Volume 34 Issue 7
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WU Jun Hui, WU Yao, WANG Zi Jing, TIAN Yao Hua, WU Yi Qun, WU Tao, WANG Meng Ying, WANG Xiao Wen, WANG Jia Ting, HU Yong Hua. Ambient Particulate Matter Pollution and Hospital Visits for Cardiac Arrhythmia in Beijing, China[J]. Biomedical and Environmental Sciences, 2021, 34(7): 562-566. doi: 10.3967/bes2021.077
Citation: WU Jun Hui, WU Yao, WANG Zi Jing, TIAN Yao Hua, WU Yi Qun, WU Tao, WANG Meng Ying, WANG Xiao Wen, WANG Jia Ting, HU Yong Hua. Ambient Particulate Matter Pollution and Hospital Visits for Cardiac Arrhythmia in Beijing, China[J]. Biomedical and Environmental Sciences, 2021, 34(7): 562-566. doi: 10.3967/bes2021.077

Ambient Particulate Matter Pollution and Hospital Visits for Cardiac Arrhythmia in Beijing, China

doi: 10.3967/bes2021.077
Funds:  This work was supported by National Natural Science Foundation of China [No. 81230066, 81473043, 81703291, 81872695]. The funding source did not play any role in the design, data collection, analysis, interpretation of data, writing, or decision to submit the article for publication
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  • Author Bio:

    WU Jun Hui, female, born in 1992, PHD Candidate, majoring in genetic epidemiology

  • Corresponding author: Professor HU Yong Hua, PHD, MD, Tel: 86-10-82801189, E-mail: yhhu@bjmu.edu.cn
  • Received Date: 2020-09-08
  • Accepted Date: 2021-02-22
  • 加载中
  • [1] Rahman F, Kwan GF, Benjamin EJ. Global epidemiology of atrial fibrillation.Nat Rev Cardiol, 2014, 11: 639-54. doi:  10.1038/nrcardio.2014.118
    [2] Inoue H, Fujiki A, Origasa H, et al. Prevalence of atrial fibrillation in the general population of Japan: an analysis based on periodic health examination. Int J Cardiol, 2009, 137: 102-7. doi:  10.1016/j.ijcard.2008.06.029
    [3] Zheng Q, Liu H, Zhang J, et al.The effect of ambient particle matters on hospital admissions for cardiac arrhythmia: a multi-city case-crossover study in China. Environ Health, 2018, 17: 60. doi:  10.1186/s12940-018-0404-z
    [4] Lu F, Xu D, Cheng Y, et al. Systematic review and meta-analysis of the adverse health effects of ambient PM2.5 and PM10 pollution in the Chinese population. Environ Res, 2015, 136: 196-204. doi:  10.1016/j.envres.2014.06.029
    [5] Song X, Liu Y, Hu Y, et al. Short-Term Exposure to Air Pollution and Cardiac Arrhythmia: A Meta-Analysis and Systematic Review[J].Int J Environ Res Public Health,2016, 13.
    [6] Xie W, Li G, Zhao D, et al. Relationship between fine particulate air pollution and ischaemic heart disease morbidity and mortality.Heart, 2015, 101: 257-63. doi:  10.1136/heartjnl-2014-306165
    [7] Wellenius GA, Burger MR, Coull BA, et al. Ambient air pollution and the risk of acute ischemic stroke[J].Arch Intern Med, 2012, 172 : 229-34. doi:  10.1001/archinternmed.2011.732
    [8] Tian Y, Liu H, Liang T, et al.Fine particulate air pollution and adult hospital admissions in 200 Chinese cities: a time-series analysis, 2019; 48, 1142−51.
    [9] Wood SN, Pya N, Säfken B J J O T a S A. Smoothing parameter and model selection for general smooth models, 2016, 111, 1548−63.
    [10] Ma YX, Yang SX, Yu Z, et al. A study on the short-term impact of fine particulate matter pollution on the incidence of cardiovascular diseases in Beijing, China. Atmospheric Environment, 2019, 215: 7.
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Ambient Particulate Matter Pollution and Hospital Visits for Cardiac Arrhythmia in Beijing, China

doi: 10.3967/bes2021.077
Funds:  This work was supported by National Natural Science Foundation of China [No. 81230066, 81473043, 81703291, 81872695]. The funding source did not play any role in the design, data collection, analysis, interpretation of data, writing, or decision to submit the article for publication
  • Author Bio:

  • Corresponding author: Professor HU Yong Hua, PHD, MD, Tel: 86-10-82801189, E-mail: yhhu@bjmu.edu.cn
WU Jun Hui, WU Yao, WANG Zi Jing, TIAN Yao Hua, WU Yi Qun, WU Tao, WANG Meng Ying, WANG Xiao Wen, WANG Jia Ting, HU Yong Hua. Ambient Particulate Matter Pollution and Hospital Visits for Cardiac Arrhythmia in Beijing, China[J]. Biomedical and Environmental Sciences, 2021, 34(7): 562-566. doi: 10.3967/bes2021.077
Citation: WU Jun Hui, WU Yao, WANG Zi Jing, TIAN Yao Hua, WU Yi Qun, WU Tao, WANG Meng Ying, WANG Xiao Wen, WANG Jia Ting, HU Yong Hua. Ambient Particulate Matter Pollution and Hospital Visits for Cardiac Arrhythmia in Beijing, China[J]. Biomedical and Environmental Sciences, 2021, 34(7): 562-566. doi: 10.3967/bes2021.077
  • Cardiac arrhythmia is a serious public health problem in many countries[1]. Previous studies estimated that 33.5 million people are affected by cardiac arrhythmia worldwide, and this number will continue to grow as society ages[2]. Despite improvements in diagnostic and therapeutic interventions in electrophysiology, the disease burden, incidence and prevalence of cardiac arrhythmia continue to increase and have aroused public health concern. Increasing evidence has indicated that air pollution may be associated with cardiac autonomic nervous system[3]. Among air pollutants, particulate matter with an aerodynamic diameter of ≤ 2.5 μm (PM2.5) is considered exert more toxicity than other air pollutants, as it provides a larger surface area and absorbs or condenses more toxic substances per unit mass[4].

    However, most of previous studies were performed in western countries where PM2.5 concentrations are much lower than those in developing countries[5]. Furthermore, these studies focused primarily on hospital admissions, which may affected by many factors like scheduled appointments and availability of hospital beds. Thus, we use a time-series design to evaluate whether PM2.5 pollution levels were related to the risk of cardiac arrhythmia between 2010 and 2012 in Beijing, China. To our knowledge, this is the first time that the short-term effects of PM2.5 levels on arrhythmia-associated outpatient visits, hospital admissions, and emergency admissions have been studied simultaneously at the city level.

    We obtained the daily numbers of hospital visits for cardiac arrhythmia from the citywide database, Beijing Medical Claim Data for Employees (BMCDE), which records medical claim data for all working or retired employees (aged ≥ 18 years) who are covered by basic medical insurance in Beijing. By the end of 2017, nearly 80% of Beijing’s residents (17.8 million) were included in the database. Basic characteristics (e.g., sex and age) of individuals diagnosed with cardiac arrhythmia were obtained from the BMCDE between January 1, 2010 and June 30, 2012 (912 days). As in previous studies, cardiac arrhythmia was identified by ICD-10 codes (Supplementary Material available in www.besjournal.com)[3]. Patients younger than 18 years old were excluded.

    Daily PM2.5 concentration data were retrieved from an air-monitoring station of the US Embassy (http://www.stateair.net) in Chaoyang District, Beijing. China did not include PM2.5 in the national first-report monitoring data until 2013; thus, the monitoring data from the US Embassy were the only open source of PM2.5 concentration data during the study period. Previous studies have reported that the PM2.5 levels detected by the US Embassy were approximately comparable with citywide PM2.5 levels in Beijing[6]. In order to reduce exposure misclassification, it could be considered that the maximum distance from the US Embassy to the hospital is about 40 km[7]. Within that radius, the monitoring data covering all the region with high population density in Beijing (> 5,000 residents/km2) and 79.2% of Beijing's residents[6]. In the present study, we used the daily average PM2.5 concentrations (24 h) as a proxy for population exposure levels. Moreover, daily meteorological data including temperature (°C) and relative humidity (%) were collected from the Chinese Meteorological Bureau.

    The association between PM2.5 concentrations and cardiac arrhythmia-associated hospital visits was assessed using a quasi-Poisson regression model, which has been widely adopted in time-series studies[8]. The following covariates were included in the main model: a penalized spline function of calendar time with 7 degrees of freedom (df) per year to control for underlying time trends, public holiday, and day of the week as categorical variables to account for short-term variations, and penalized spline functions with 3 df for temperature and 3 df for relative humidity. The formula applied in the present study is as follows:

    $$\begin{split} {\rm{Log}}\left[ {{{E}}\left( {{{{Y}}_{{t}}}} \right)} \right] = \alpha & + \beta {\rm{P}}{{\rm{M}}_{2.5}} + {\rm{day}}\;{\rm{of}}\;{\rm{the}}\;{\rm{week}}\\ & + {\rm{public}}\;{\rm{holiday}}\\ & + s\left( {{\rm{calendar}}\;{\rm{time}},\;7\;{\rm{per}}\;{\rm{year}}} \right) \\ &+ s\left( {{\rm{temperature}},3} \right)\\ & + s\left( {{\rm{humidit}}{{\rm{y}}_{01}},3} \right) \end{split}$$

    where ${{{E}}\left( {{{{Y}}_{{t}}}} \right)} $ refers to the expected number of cardiac arrhythmia-associated hospital visits on day t, α represents the model intercept, β denotes the log (relative risk) of morbidity relative to unit increase in PM2.5 level; and s represents a smoother based on the penalized splines. Following the approaches applied in previous studies, we selected the degrees of freedom (df) for calendar time, temperature, and relative humidity[3].

    We applied a penalized cubic regression spline of the PM2.5 concentration with 3 df to assess the concentration-response association. We also explored the relationship between PM2.5 and cardiac arrhythmia-associated hospital visits by building models with a single-day lag from the current day (lag 0) up to the previous 3 days (lag 1, lag 2, and lag 3), and with 2-day (lag 0–1), 3-day (lag 0–2), and 4-day (lag 0–3) moving average concentrations. To examine potential effects per subgroup, analyses were stratified by age, sex, and season. The warm season was defined as April to September, and the cool season was defined as October to March. We used the Z-test to assess the statistical significance of the subgroup differences.

    All results were presented as the percentage change and 95% CI of the daily cardiac arrhythmia-associated hospital visits for each 10-μg/m3 increase in ambient PM2.5. We applied the “mgcv” and “nlme” packages in R 3.2.2 for all the analyses[9].

    In total, 1,435,139 outpatient visits, 29,837 hospital admissions, and 43,347 emergency visits between January 1, 2010 to June 30, 2012 were identified from the BMCDE database. Table 1 summarizes the descriptive statistics for the cardiac arrhythmia-associated hospital visits, PM2.5 concentrations, and weather conditions. The daily mean counts for the outpatient visits, hospital admissions and emergency visits were 1,573 (1,132), 33 (22), and 48 (27) respectively. For PM2.5 concentration, the annual average was 99.5 (75.3) μg/m3, and the maximum was 493.0 μg/m3.

    VariableMean ± SDPercentiles
    MinimumP25P50P75Maximum
    Outpatient visits1,573 ± 1,13215751,3912,3045,055
     Cool season1,565 ± 1,23214391,4702,4735,055
     Warm season1,587 ± 96617771,3482,2494,124
    Hospital admissions33 ± 2215395184
     Cool season34 ± 3015395284
     Warm season43 ± 2115394981
    Emergency visits48 ± 271284866120
     Cool season49 ± 291245271120
     Warm season46 ± 228294357107
    PM2.5 (μg/m3)99.5 ± 75.37.242.582.8133.0493.0
    Temperature (℃)12.6 ± 11.6−12.51.514.123.834.5
    Relative humidity (%)48.6 ± 20.3930486692
      Note. SD: standard deviation.

    Table 1.  Summary statistics for daily cardiac arrhythmia-associated hospital visits, daily PM2.5 concentrations and meteorological data

    Table 2 presents the acute elevations in PM2.5 concentrations were related to increased hospital visits for cardiac arrhythmia. A 10-μg/m3 increase in PM2.5 level on lag days 0–3 corresponded with 0.71% (95% CI: 0.43%–0.47%) and 0.48% (95% CI: 0.59%–0.82%) increases in outpatient and hospital admissions for cardiac arrhythmia, respectively. A 10 μg/m3 increase in PM2.5 level on current day corresponded with 0.17% (95% CI: 0.10%–0.23%) increases in emergency visits for cardiac arrhythmia. Our findings provide new evidence which may help improve targeted intervention strategies for cardiac arrhythmia in China. Previous western studies have explored associations between PM2.5 and hospitalizations for cardiac arrhythmia, which support the results of our study. A recent meta-analysis of PM2.5 and daily hospitalizations for cardiac arrhythmia reported that arrhythmia-associated hospitalizations were related to increases in PM2.5 (relative risk = 1.02 per 10 μg/m3)[5]. However, most of previous studies have been conducted in the US and Europe, while Beijing has higher PM2.5 levels than those areas, which might lead to differences in effect estimates.

    Hospital visitsLag daysPercentage change (%)95% Confidence interval (%)P value
    Outpatient visits00.150.17–0.19< 0.001
    10.510.19–0.22< 0.001
    20.480.25–0.27< 0.001
    30.260.16–0.18< 0.001
    0–10.390.24–0.27< 0.001
    0–20.640.38–0.41< 0.001
    0–30.710.43–0.47< 0.001
    Hospital admissions00.180.07–0.22< 0.001
    10.210.42–0.60< 0.001
    20.260.40–0.56< 0.001
    30.170.18–0.340.001
    0–10.260.30–0.49< 0.001
    0–20.400.53–0.75< 0.001
    0–30.450.59–0.82< 0.001
    Emergency visits00.170.10–0.230.012
    1−0.110.10 to −0.030.173
    2−0.26−0.33 to −0.190.100
    3−0.11−0.18 to −0.040.098
    0–10.07−0.01 to −0.160.380
    0–2−0.09−0.19 to −0.010.345
    0–3−0.15−0.26 to −0.050.154

    Table 2.  Percentage change with 95% confidence interval in cardiac arrhythmia-associated hospital visits for each 10 μg/m3 increase in PM2.5 levels for different lag days

    Table 3 lists the estimates for subgroup analyses. The association between PM2.5 and arrhythmia-associated outpatient visits was greater during the warm season (0.94%, 95% CI: 0.91%–0.97%), and the estimated PM2.5 effect was stronger in men (0.82%, 95% CI: 0.66%–0.99%). For hospital admissions, the estimates were higher for men (0.48%, 95% CI: 0.45%–0.51%) and during the warm season (0.52%, 95% CI: 0.50%–0.54%). For emergency visits, the estimates were greater for men (0.19%, 95% CI: 0.10%–0.29%) and during the warm season (0.22%, 95% CI: 0.14%–0.30%). Similarly, a recent study reported that the short-term effect of PM2.5 on arrhythmias was relatively stronger for men than for women in all lag models[10], but the underlying mechanism of the sex difference remains elusive and requires more study. Differences in seasonal estimates may be due to the behavioral differences. Beijing residents are more likely to participate in outdoor activities and ventilate their homes during the warm season, bringing monitoring data closer to their individual exposure levels. Another explanation for the higher correlation is that high temperatures may affect the chemical conversion and deposition processes of air pollutants.

    Hospital visitsPercentage change (%)95% CI (%)P Pa
    Outpatient visits
     Sex< 0.001
      Male0.820.66–0.99< 0.001
      Female0.650.48–0.83< 0.001
     Age (years)0.010
      < 650.910.71–1.10< 0.001
      ≥ 650.670.52–0.82< 0.001
     Season0.014
      Cool0.640.38–0.90< 0.001
      Warm0.940.91–0.97< 0.001
    Hospital admissions
     Sex0.017
      Male0.480.45–0.51< 0.001
      Female0.420.40–0.45< 0.001
     Age (years)< 0.001
      < 650.390.36–0.42< 0.001
      ≥ 650.500.48–0.53< 0.001
     Season0.029
      Cool0.390.35–0.42< 0.001
      Warm0.520.50–0.54< 0.001
    Emergency visits
     Sex0.004
      Male0.190.10–0.290.044
      Female0.140.04–0.230.140
     Age (years)0.016
      < 650.270.17–0.370.006
      ≥ 650.08−0.01 to −0.170.376
     Season0.025
      Cool−0.21−0.36 to −0.070.139
      Warm0.220.14 to −0.300.004
      Note. aP: Z-test for the difference between the two risk estimates in subgroup analyses.

    Table 3.  Increases in cardiac arrhythmia-associated hospital visits for each 10 μg/m3 increase in PM2.5 for lag days 0–3 (for outpatient visits and hospital admissions) and current-day (for emergency visits) with stratification

    In the present citywide time-series analysis, significant and positive associations between PM2.5 levels and hospital visits for cardiac arrhythmia were found in Beijing. To our knowledge, this is the first citywide research in Beijing, or even in other highly air polluted region, to comprehensively reveal the acute effect of PM2.5 on cardiac arrhythmia-associated outpatient, emergency, and hospital admissions in a same study.

    Some limitations should be acknowledged. First, data from one fixed monitoring station could not exactly represent the actual situation of personal exposure to PM2.5. Second, because the information was limited, we did not explore other potential modifiers, including health-related and nutritional factors, which are reported to be associated with arrhythmias[3]. Third, the US Embassy only provided PM2.5 monitoring data during the study period. The lack of authoritative records of other air pollutants has limited our exploration of the independent effects of PM2.5. Finally, due to information limitations, we are unable to distinguish all subtypes of arrhythmias. Future research is warranted to investigate the modification effect between different cardiac arrhythmia subtypes.

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