Correlation of PM<sub>2.5</sub> pollution and daily mortality rate of cardiovascular and cerebrovascular diseases in Northeast China through PM<sub>2.5</sub> sources analysis

Qianqi Hong; Yang Zhao; Jing Wang; Hongyan Sun; Lanxin Deng; Jingjing Cao; Cheng Wang

doi:10.1515/fzm-2024-0019

Correlation of PM_2.5 pollution and daily mortality rate of cardiovascular and cerebrovascular diseases in Northeast China through PM_2.5 sources analysis

doi: 10.1515/fzm-2024-0019

Qianqi Hong^{1, 2, #},
Yang Zhao^{1, #},
Jing Wang^{1, #},
Hongyan Sun¹,
Lanxin Deng¹,
Jingjing Cao¹,
Cheng Wang^{1
, ,}

1.
Department of Environmental Hygiene, School of Public Health, Harbin Medical University, Harbin 150081, China
2.
Harbin Center for Disease Control and Prevention, Harbin 150056, China

Funds:

the National Natural Science Foundation of China 82273613

the Research project of Health Commission of Heilongjiang Province 20231212010393

More Information

Corresponding author: Cheng Wang, E-mail: wangchenghlj@163.com

摘要

Abstract: Objective This study aims to evaluate the relationship between PM_2.5 concentration and daily mortality rate from cardiovascular and cerebrovascular diseases (CCVD) in cold regions of northern China, as well as to identify the primary sources of PM_2.5. Methods A time series analysis model was used to calculate the exposure-response relationship between PM_2.5 and CCVD mortality in Harbin. Positive matrix factorization (PMF) was employed to analyze the sources of PM_2.5. Results After adjusting for multiple pollutant combinations, the maximum excess risk of cardio-cerebrovascular death on the day of PM_2.5 exposure was 0.42% (95% CI: 0.15%-0.70%). Stratification by gender and age revealed that the elderly individuals and men were particularly susceptible to PM_2.5 exposure. The source analysis identified seven major pollution sources contributing to PM_2.5 in Harbin. Conclusion Our findings strengthen the evidence that PM_2.5 is an independent risk factor for daily CCVD mortality, identify vulnerable populations that require special attention, and pinpoint the primary sources of PM_2.5 in Harbin. These findings provide reference points for effectively reducing the health risks associated with PM_2.5 exposure.
- PM_2.5 /
- cardio-cerebrovascular diseases /
- daily mortality /
- time series /
- PMF

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Figure 1. Correlation analysis between air pollutants and meteorological factors

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Figure 2. Component spectra of each factor obtained by positive matrix factorization

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Figure 3. Contribution rates of each factor obtained by positive matrix factorization

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Table 1. Description of meteorological data, air pollution data and CCVD data of Harbin City from 2016 to 2018

Year	2016			2017			2018			Standard value
	Mean ± SD	Min	Max	Mean ± SD	Min	Max	Mean ± SD	Min	Max
Temperature (℃)	1.05 ± 16.36	-33.5	25.3	5.23 ± 15.22	-22.38	29.15	5.19 ± 15.79	-29.4	30.8	-
Air pressure (hpa)	995.57 ± 9.68	967.4	1021.8	999.69 ± 8.95	977.1	1020	1000.27 ± 9.46	979.2	1025.4	-
Relative humidity (%)	67.66 ± 14.78	28	98	63.62 ± 14.68	19	95	64.05 ± 15.94	20.3	95	-
Wind velocity (m/s)	2.89 ± 1.47	0.2	9	2.99 ± 1.40	0	9.2	2.97 ± 1.20	0.8	8.1	-
SO₂ (μg/m³)	27.53 ± 23.70	2.82	101.18	24.19 ± 20.49	4.73	107.45	18.81 ± 16.53	3.45	80	150
NO₂ (μg/m³)	42.05 ± 15.9	16.45	134.36	42.64 ± 19.07	11.82	130.45	33.71 ± 13.41	12.91	91.82	80
CO (mg/m³)	1.14 ± 0.37	0.54	3.34	1.03 ± 0.58	0.28	3.65	0.74 ± 0.30	0.38	2.36	4
O₃ (μg/m³)	62.97 ± 25.55	12.73	159.09	85.23 ± 34.22	27.91	229.73	75.05 ± 29.10	25	192.64	160
PM_2.5 (μg/m³)	54.12 ± 42.84	8	211.64	57.16 ± 62.92	6.45	460.45	37.37 ± 35.57	4.91	263.55	75
CCVD (n)	92.04 ± 14.60	56	153	92.98 ± 13.77	60	135	89.02 ± 15.07	51	134	-

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Table 2. Association between PM_2.5 and CCVD mortality with a 10mg/m³ increase in PM_2.5: sex-specific, age-specific, and total analysis for Harbin city from 2016 to 2018

lag days	Sex				Age				Total People
	Male		Female		Age < 65		Age ≥ 65
	ER	95%CI	ER	95%CI	ER	95%CI	ER	95%CI	ER	95%CI
lag0	0.24	(-0.02, 0.49)	0.37^*	(0.09, 0.65)	0.37^*	(0.02, 0.71)	0.27^*	(0.03, 0.50)	0.29^*	(0.09, 0.50)
lag1	0.28^*	(0.02, 0.53)	0.15	(-0.13, 0.44)	0.26	(-0.08, 0.61)	0.21	(-0.02, 0.45)	0.23^*	(0.02, 0.43)
lag2	0.39^*	(0.14, 0.63)	0.30^*	(0.02, 0.58)	0.28	(-0.06, 0.62)	0.37^*	(0.15, 0.60)	0.35^*	(0.15, 0.55)
lag3	0.2	(-0.05, 0.45)	0.1	(-0.18, 0.38)	0.09	(-0.25, 0.43)	0.18	(-0.05, 0.41)	0.16	(-0.05, 0.36)
lag4	0.27^*	(0.02, 0.51)	0.05	(-0.22, 0.33)	-0.20	(-0.54, 0.14)	0.32^*	(0.09, 0.54)	0.18	(-0.03, 0.38)
lag5	0.31^*	(0.06, 0.56)	0.29^*	(0.01, 0.57)	0.16	(-0.18, 0.50)	0.35^*	(0.13, 0.58)	0.30^*	(0.10, 0.50)
lag6	0.20	(-0.05, 0.45)	0.11	(-0.17, 0.39)	0.15	(-0.19, 0.49)	0.16	(-0.07, 0.40)	0.16	(-0.04, 0.37)
lag7	0.25	(0.00, 0.50)	0.12	(-0.16, 0.40)	-0.04	(-0.38, 0.31)	0.28^*	(0.05, 0.51)	0.19	(-0.01, 0.40)
CI, confidence interval; ER, relative risk. ^*P < 0.05..

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Table 3. Association between PM2.5 and CCVD mortality with a 10mg/m3 increase in PM2.5 : single-pollutant and multi-pollutant models for Harbin city from 2016 to 2018

Models	lag0		lag1		lag2		lag5
	ER	95%CI	ER	95%CI	ER	95%CI	ER	95%CI
PM_2.5	0.29^*	(0.09, 0.50)	0.23^*	(0.02, 0.43)	0.35^*	(0.15, 0.55)	0.30^*	(0.10, 0.50)
PM_2.5 + NO₂	0.42^*	(0.15, 0.69)	0.20	(-0.06, 0.47)	0.19	(-0.07, 0.46)	0.29^*	(0.02, 0.55)
PM_2.5 + SO₂	0.41^*	(0.18, 0.65)	0.27^*	(0.03, 0.50)	0.29^*	(0.06, 0.53)	0.27^*	(0.03, 0.50)
PM_2.5 + O₃	0.29^*	(0.08, 0.50)	0.18	(-0.02, 0.39)	0.30^*	(0.10, 0.50)	0.29^*	(0.08, 0.49)
PM_2.5 + CO	0.35^*	(0.08, 0.63)	0.17	(-0.10, 0.44)	0.18	(-0.09, 0.44)	0.14	(-0.13, 0.41)
PM_2.5 + NO₂ + SO₂	0.42^*	(0.15, 0.70)	0.21	(-0.06, 0.47)	0.19	(-0.07, 0.46)	0.28^*	(0.01, 0.55)
PM_2.5 + NO₂ + CO	0.41^*	(0.12, 0.70)	0.17	(-0.11, 0.46)	0.14	(-0.14, 0.42)	0.19	(-0.09, 0.47)
PM_2.5 + NO₂ + O₃	0.41^*	(0.14, 0.69)	0.15	(-0.12, 0.42)	0.14	(-0.13, 0.40)	0.27	(0, 0.54)
PM_2.5 + SO₂ + CO	0.39^*	(0.11, 0.66)	0.18	(-0.09, 0.46)	0.17	(-0.09, 0.44)	0.15	(-0.12, 0.42)
PM_2.5 + SO₂ + O₃	0.41^*	(0.17, 0.65)	0.22	(-0.02, 0.45)	0.24	(0, 0.47)	0.25^*	(0.01, 0.49)
PM_2.5 + CO + O₃	0.35^*	(0.07, 0.62)	0.11	(-0.16, 0.39)	0.11	(-0.15, 0.38)	0.13	(-0.14, 0.39)
PM_2.5 + NO₂ +SO₂+CO	0.40^*	(0.11, 0.69)	0.17	(-0.12, 0.45)	0.14	(-0.14, 0.42)	0.19	(-0.09, 0.47)
PM_2.5 + NO₂ +SO₂+O₃	0.42^*	(0.15, 0.69)	0.16	(-0.11, 0.43)	0.14	(-0.13, 0.40)	0.27	(0, 0.54)
PM_2.5 + NO₂ +O₃+CO	0.41^*	(0.12, 0.70)	0.12	(-0.17, 0.40)	0.08	(-0.20, 0.36)	0.17	(-0.11, 0.46)
PM_2.5 + SO₂ +O₃+CO	0.38^*	(0.11, 0.66)	0.13	(-0.14, 0.40)	0.11	(-0.16, 0.38)	0.13	(-0.14, 0.40)
PM_2.5 + NO₂ +SO₂+CO+O₃	0.40^*	(0.11, 0.69)	0.11	(-0.17, 0.40)	0.08	(-0.21, 0.36)	0.17	(-0.11, 0.46)
CI, confidence interval; ER, relative risk. ^*P < 0.05.

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