Associations of Early-Life Exposure to Submicron Particulate Matter With Childhood Asthma and Wheeze in China

Chuansha Wu; Yunquan Zhang; Jing Wei; Zhuohui Zhao; Dan Norbäck; Xin Zhang; Chan Lu; Wei Yu; Tingting Wang; Xiaohong Zheng; Ling Zhang

doi:10.1001/jamanetworkopen.2022.36003

. 2022 Oct 11;5(10):e2236003. doi: 10.1001/jamanetworkopen.2022.36003

Associations of Early-Life Exposure to Submicron Particulate Matter With Childhood Asthma and Wheeze in China

Chuansha Wu ^1,², Yunquan Zhang ^2,^3,^✉, Jing Wei ⁴, Zhuohui Zhao ⁵, Dan Norbäck ⁶, Xin Zhang ⁷, Chan Lu ⁸, Wei Yu ⁹, Tingting Wang ¹⁰, Xiaohong Zheng ¹¹, Ling Zhang ^1,^2,^✉

¹Department of Environmental Hygiene and Occupational Medicine, School of Public Health, Medical College, Wuhan University of Science and Technology, Wuhan, China

²Hubei Province Key Laboratory of Occupational Hazard Identification and Control, Wuhan University of Science and Technology, Wuhan, China

³Department of Epidemiology and Biostatistics, School of Public Health, Medical College, Wuhan University of Science and Technology, Wuhan, China

⁴Department of Chemical and Biochemical Engineering, Iowa Technology Institute, The University of Iowa, Iowa City

⁵Department of Environmental Health, School of Public Health, Fudan University, Shanghai, China

⁶Department of Medical Sciences, Uppsala University, Uppsala, Sweden

⁷Research Centre for Environmental Science and Engineering, Shanxi University, Taiyuan, China

⁸Department of Occupational and Environmental Health, School of Public Health, Xiangya Medical College, Central South University, Changsha, China

⁹Joint International Research Laboratory of Green Buildings and Built Environments, Ministry of Education, Chongqing University, Chongqing, China

¹⁰School of Nursing and Health Management, Shanghai University of Medicine and Health Sciences, Shanghai, China

¹¹School of Energy and Environment, Southeast University, Nanjing, China

Accepted for Publication: August 25, 2022.

Published: October 11, 2022. doi:10.1001/jamanetworkopen.2022.36003

^✉

Corresponding Authors: Yunquan Zhang, PhD, (YunquanZhang@wust.edu.cn), and Ling Zhang, PhD (zhangling@wust.edu.cn), School of Public Health, Wuhan University of Science and Technology, #2 Huangjiahu W Rd, Qingling Street, Hongshan District, Wuhan 430065, China.

Author Contributions: Drs Wu and Y. Zhang contributed equally to this work. Drs Y. Zhang and L. Zhang had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Y. Zhang, Zhao, Dan, X. Zhang, Yu, L. Zhang.

Acquisition, analysis, or interpretation of data: Wu, Y. Zhang, Wei, Dan, Lu, Wang, Zheng.

Drafting of the manuscript: Wu, Wang.

Critical revision of the manuscript for important intellectual content: Y. Zhang, Wei, Zhao, Dan, X. Zhang, Lu, Yu, Zheng, L. Zhang.

Statistical analysis: Y. Zhang, X. Zhang, Wang.

Obtained funding: Zhao, Lu, L. Zhang.

Administrative, technical, or material support: Wei, Zhao, Lu, Yu, Wang, L. Zhang.

Supervision: Y. Zhang, Dan, X. Zhang, Zheng, L. Zhang.

Conflict of Interest Disclosures: None reported.

Funding/Support: This work was supported by grant T2020003 from the Outstanding Young and Middle-aged Technology Innovation Team Project of Hubei Provincial Department of Education (Dr L. Zhang) and grants 81861138005 (Dr Zhao) and 42007391 (Dr Lu) from the Natural Science Foundation of China.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, ‘management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: We thank all the participants and collaborators of the China, Children, Homes, Health study.

^✉

Corresponding author.

PMCID: PMC9554703 PMID: 36219442

This cross-sectional study examines the association of early-life exposure to particulate matter of varying particle sizes with asthma and wheeze among children aged 3 to 6 years in 7 cities in China.

Key Points

Question

Is early-life exposure to particulate matter (PM), especially with an aerodynamic equivalent diameter of 1 μm or less (ie, PM₁), associated with increased risk of childhood asthma?

Findings

In this cross-sectional study of 29 418 Chinese children aged 3 to 6 years, early-life PM₁, PM_2.5, and PM₁₀ exposure was associated with increased risk of childhood asthma, with higher estimates for smaller particles. Moreover, PM₁ rather than PM_1-2.5 contributed to the association between PM_2.5 and asthma.

Meaning

The findings suggest that PM with smaller particles may be more toxic to the respiratory system than PM with larger particles; health care policy makers should pay more attention to early-life PM₁ exposure to reduce childhood asthma associated with PM.

Abstract

Importance

Exposure to particulate matter (PM) has been associated with childhood asthma and wheeze. However, the specific associations between asthma and PM with an aerodynamic equivalent diameter of 1 μm or less (ie, PM₁), which is a contributor to PM_2.5 and potentially more toxic than PM_2.5, remain unclear.

Objective

To investigate the association of early-life (prenatal and first year) exposure to size-segregated PM, including PM₁, PM_1-2.5, PM_2.5, PM_2.5-10, and PM₁₀, with childhood asthma and wheeze.

Design, Setting, and Participants

This cross-sectional study was based on a questionnaire administered between June 2019 and June 2020 to caregivers of children aged 3 to 6 years in 7 Chinese cities (Wuhan, Changsha, Taiyuan, Nanjing, Shanghai, Chongqing, and Urumqi) as the second phase of the China, Children, Homes, Health study.

Exposures

Exposure to PM₁, PM_1-2.5, PM_2.5, PM_2.5-10, and PM₁₀ during the prenatal period and first year of life.

Main Outcomes and Measures

The main outcomes were caregiver-reported childhood asthma and wheeze. A machine learning–based space-time model was applied to estimate early-life PM₁, PM_2.5, and PM₁₀ exposure at 1 × 1-km resolution. Concentrations of PM_1-2.5 and PM_2.5-10 were calculated by subtracting PM₁ from PM_2.5 and PM_2.5 from PM₁₀, respectively. Multilevel (city and child) logistic regression models were applied to assess associations.

Results

Of 29 418 children whose caregivers completed the survey (15 320 boys [52.1%]; mean [SD] age, 4.9 [0.9] years), 2524 (8.6%) ever had wheeze and 1161 (3.9%) were diagnosed with asthma. Among all children, 18 514 (62.9%) were breastfed for more than 6 months and 787 (2.7%) had parental history of atopy. A total of 22 250 children (75.6%) had a mother with an educational level of university or above. Of the 25 422 children for whom information about cigarette smoking exposure was collected, 576 (2.3%) had a mother who was a current or former smoker during pregnancy and 7525 (29.7%) had passive household cigarette smoke exposure in early life. Early-life PM₁, PM_2.5, and PM₁₀ exposure were significantly associated with increased risk of childhood asthma, with higher estimates per 10-μg/m³ increase in PM₁ (OR, 1.55; 95% CI, 1.27-1.89) than in PM_2.5 (OR, 1.14; 95% CI, 1.03-1.26) and PM₁₀ (OR, 1.11; 95% CI, 1.02-1.20). No association was observed between asthma and PM_1-2.5 exposure, suggesting that PM₁ rather than PM_1-2.5 contributed to the association between PM_2.5 and childhood asthma. There were significant associations between childhood wheeze and early-life PM₁ exposure (OR, 1.23; 95% CI, 1.07-1.41) and PM_2.5 exposure (OR, 1.08; 95% CI, 1.01-1.16) per 10-μg/m³ increase in PM₁ and PM_2.5, respectively.

Conclusions and Relevance

In this cross-sectional study, higher estimates were observed for the association between PM with smaller particles, such as PM₁, vs PM with larger particles and childhood asthma. The results suggest that the association between PM_2.5 and childhood asthma was mainly attributable to PM₁.

Introduction

Ambient particulate matter (PM) pollution has aroused great interest and attention from all over the world because of its association with a substantial global burden of disease.^1,2,3,4 Although air quality in China has improved in recent years, PM exposure levels were still associated with approximately 1.4 million deaths in China in 2019.⁵ Recent epidemiological studies indicated that long-term and short-term PM exposure have positive associations with respiratory disease in vulnerable populations, such as children.^6,7

Asthma is the most common chronic respiratory disease in children, with a trend of increasing prevalence.^8,9,10,11 The increase in prevalence of asthma may be associated with environmental factors independently or combined with genetic factors.^12,13,14,15

Previous studies estimated that PM₁ (PM with an aerodynamic equivalent diameter ≤1 μm) is a major contributor (approximately 80%) to the concentration of PM_2.5 (PM with an aerodynamic equivalent diameter ≤2.5 μm) in China.^16,17,18 Emerging evidence indicated that the particle size of PM was inversely associated with lung toxic effects.^19,20 To our knowledge, only 2 epidemiological studies have reported a positive association between PM₁ exposure and childhood asthma, perhaps because PM₁ is not routinely monitored worldwide. One of these studies estimated PM₁ exposure at 10 × 10-km resolution,²¹ which may be subject to exposure misclassifications. The other was a single-city study,²² although the vast territory of China makes it hard to generalize results from a single city to the whole country. Moreover, previous studies did not elucidate whether the associations between PM_2.5 and asthma were mainly owed to the contribution of PM₁. Within a multicity population, we intended to investigate the association of exposure to 1 × 1-km high-resolution, size-segregated PM (PM₁, PM_1-2.5 [aerodynamic equivalent diameter >1 and ≤2.5 μm], PM_2.5, PM_2.5-10 [aerodynamic equivalent diameter >2.5 μm and ≤10 μm], and PM₁₀ [aerodynamic equivalent diameter ≤10 μm]) prenatally and during the first year of life with childhood asthma and wheeze among children aged 3 to 6 years in China.

Methods

Study Population

In this cross-sectional study, from June 2019 to June 2020, a questionnaire investigation was conducted in 7 major cities in China, including Wuhan, Changsha, Taiyuan, Nanjing, Shanghai, Chongqing, and Urumqi, as the second phase of the China, Children, Homes, Health (CCHH) study.²³ A standardized questionnaire was previously validated by a pilot study and was used in the CCHH study with written consent from the parents or legal guardians.²⁴ Ethics approval for the current study was acquired from the ethical committee of the School of Public Health, Fudan University. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.

We applied a multistage cluster sampling method to choose the surveyed groups of children; the specific description of the sampling methods was provided in previous articles.^22,25 The caregivers of children aged 3 to 6 years from 5 cities (Wuhan, Changsha, Taiyuan, Nanjing, and Shanghai) completed the standard electronic questionnaire, whereas Chongqing and Urumqi used traditional paper questionnaires to collect data. We excluded participants whose residential address was outside the survey city, children who were conceived before January 1, 2013 (the individual PM exposure was available in the 7 cities after 2013), mothers with unknown gestational time and basic covariates, and children born at less than 28 weeks’ gestation.

Exposure Assessment

A mature machine learning–based method (an enhanced space-time extremely randomized trees model) was used to estimate the daily mean concentrations of ambient PM₁, PM_2.5, and PM₁₀ in the 7 cities from January 2013 to December 2018, with a spatial resolution of 1 km.^{26,27,28,29,30} We further calculated the concentrations of PM_1-2.5 and PM_2.5-10 by subtracting the concentration of PM₁ from PM_2.5 and PM_2.5 from PM₁₀, respectively. The detailed descriptions of the space-time extremely randomized trees model are provided in the eMethods in the Supplement. The validation results were of high quality, with a cross-validation coefficient of determination (CV – R²) of 0.77 for PM₁,²⁷ 0.92 for PM_2.5,²⁹ and 0.86 for PM₁₀³⁰ for monthly predicted estimates, and the corresponding root mean square errors of ground measurements were 4.8 μg/m³, 5.1 μg/m³, and 11.1 μg/m³, respectively. We collected daily in situ measurements of PM₁ from the China Atmosphere Watch Network and ground-based monitoring data of daily PM_2.5 and PM₁₀ from the China National Urban Air Quality Real-Time Publishing Platform from 2013 to 2018. The method of model development in this study was detailed by some of us in previous studies.^27,28,29,30

For each participant in the present study, we first retrieved monthly mean concentrations of size-segregated particles from 2013 to 2018 from the 1 × 1-km gridded estimates based on the participant’s residential address. Monthly estimates were then used to calculate the mean exposure in early life (from the beginning of pregnancy through the first year of life) by further considering information on birth and conception dates. To reduce exposure misclassification, prenatal and first-year exposure of ambient PM was assigned based on the corresponding address information for each period.

Respiratory Health Outcomes

The standard questionnaire, which was modified from the questionnaire of the International Study of Asthma and Allergies in Childhood,³¹ was used to collect information on lifetime-ever asthma and lifetime-ever wheeze. Participants were asked the following 2 questions: (1) “Has your child ever had doctor-diagnosed asthma?” and (2) “Has your child ever had wheezing or whistling in the chest at any time in the past?”

Covariates

Based on the articles previously published by the CCHH study^32,33,34 and relevant literature,^12,13,35 we selected the following 3 groups of covariates: (1) characteristics of the child, including sex (male or female), age, ethnicity (self-identified by respondents as Han or minority nationalities and included as a covariate because this was a multicity study and there are 55 minority nationalities in China besides Han ethnicity), delivery mode (vaginal or cesarean), birth season (spring [March to May], summer [June to August], autumn [September to November], or winter [December to February]), and breastfeeding duration (<1 month, 1 month to <6 months, 6 months to <12 months, or ≥12 months); (2) characteristics of the parents, including maternal educational level (high school or below, university, or postgraduate or above), maternal smoking status (never, former, or current) and parental history of atopy (yes or no); and (3) characteristics of the household environment, including passive smoke exposure, air pollution from solid fuel, house renovation, and visible mold or dampness. The 4 household environment variables were classified as none, prenatal exposure, first-year exposure, or both.

Statistical Analysis

Spearman correlation coefficients were calculated between pairs of size-segregated PM measures in different periods. First, multilevel (city and child) logistic regression models were applied to assess the associations of early-life (prenatal and first year) exposure to size-segregated particles with childhood asthma and wheeze. Size-segregated PM categories (PM₁, PM_1-2.5, PM_2.5, PM_2.5-10, and PM₁₀) were included in the models separately. We started with the crude models (model 1); gradually added the characteristics of the child (models 2, 3, and 4), parent (models 3 and 4), and household environment (model 4); and obtained the results from the 4 models. The participants’ city was included as a random intercept in all regression models. The method of addressing missing values is provided in the eMethods in the Supplement. Based on the results of model 4, further analyses were carried out. Restricted cubic spline functions were conducted to explore the exposure-response relationships between early-life exposure to size-segregated particles and childhood asthma and wheeze. Visual inspection and a likelihood ratio test were used to examine the nonlinearity in exposure-response relationships. In addition, we further applied multilevel (city and child) logistic regression models to separately investigate the associations of prenatal and first-year exposure to size-segregated particles with childhood asthma and wheeze. Associations were calculated as odds ratios (ORs) with 95% CIs for each 10-μg/m³ increase in the concentration of size-segregated particles to which children were exposed. The detailed descriptions of sensitivity analyses are provided in the eMethods in the Supplement.

All statistical analyses were performed using R, version 4.0.0 (R Project for Statistical Computing). We conducted 2-sided tests and considered P < .05 as statistically significant.

Results

Characteristics of Study Population

Among 38 911 children aged 3 to 6 years, the caregivers of 37 858 (response rate, 97.3%) successfully filled out the questions for childhood asthma and wheeze; of these, we excluded 4405 children (11.6%) whose residential address was outside the survey city; 1971 (5.2%) who were conceived before January 1, 2013; 1652 (4.4%) who had a mother with unknown gestational time and basic covariates; and 412 (1.1%) who were born at less than 28 weeks’ gestation, leaving 29 418 children (77.7%) for further analyses.

Of the 29 418 included children (15 320 boys [52.1%] and 14 098 girls [47.9%]; mean [SD] age, 4.9 [0.9] years), 2524 (8.6%) were identified by their caregiver as ever having wheeze and 1161 (3.9%) were diagnosed with asthma (Table). Among all children, 15 213 (51.7%) were born vaginally, 1551 (5.3%) were preterm births, 1023 (3.5%) were low birth weight, 18 514 (62.9%) were breastfed for more than 6 months, and 787 (2.7%) had parental history of atopy. A total of 22 250 children (75.6%) had a mother with an educational level of university or above, and 576 of 25 422 children (2.3%) had a mother who was a current or former smoker during pregnancy. For household environment, 7525 of 25 422 children (29.6%) had passive cigarette smoke exposure (this information was not collected for children from Urumqi [n = 3996]). Households of 5538 of 23 548 children (23.5%) had house renovation, and households of 4440 of 23 548 (18.9%) had visible mold or dampness in the child’s early life (this information was not collected for children from Urumqi [n = 3996] or Chongqing [n = 1874]).

Table. Characteristics of Children, Parents, and Household Environment in the Study.

Characteristic	Children (N = 29 418)^a
Outcome
Diagnosed with asthma	1161 (3.9)
Ever had wheeze	2524 (8.6)
Child
Sex
Boy	15 320 (52.1)
Girl	14 098 (47.9)
Age, mean (SD), y	4.9 (0.9)
Han ethnicity	27 882 (94.8)
Vaginal birth	15 213 (51.7)
Born in warm season (April to September)	14 834 (50.4)
Preterm birth	1551 (5.3)
Low birth weight	1023 (3.5)
Breastfeeding duration >6 mo	18 514 (62.9)
Parent
Maternal educational level of university or above	22 250 (75.6)
Maternal smoking status (current or former)^b	576/25 422 (2.3)
Parental history of atopy	787 (2.7)
Household environment
Passive cigarette smoke exposure^b	7525/25 422 (29.6)
Air pollution from solid fuel	267 (0.9)
House renovation during pregnancy or first year of life^c	5538/23 548 (23.5)
Visible mold or dampness during pregnancy or first year of life^c	4440/23 548 (18.9)

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^{^a}

Data are presented as number (percentage) of children unless otherwise indicated.

^{^b}

Urumqi (n = 3996) did not collect information for this variable.

^{^c}

Urumqi (n = 3996) and Chongqing (n = 1874) did not collect information for this variable.

Concentrations and Correlations of PM

As shown in eTable 1 in the Supplement, the mean (SD) early-life exposure to PM₁ was 36.7 (8.9) μg/m³, to PM_1-2.5 was 20.7 (4.6) μg/m³, to PM_2.5 was 61.7 (13.1) μg/m³, to PM_2.5-10 was 48.9 (16.6) μg/m³, and to PM₁₀ was 110.6 (19.3) μg/m³. The concentrations of size-segregated particles were higher during pregnancy and then showed a decreasing trend in the first year of life, with a mean (SD) decrease of 3.9 (6.6) μg/m³ for PM₁, 1.9 (6.8) μg/m³ for PM_1-2.5, 7.2 (12.2) μg/m³ for PM_2.5, 3.5 (10.7) μg/m³ for PM_2.5-10, and 10.6 (17.5) μg/m³ for PM₁₀. The concentrations of size-segregated particles in different periods (early life, prenatal, and first year) were highly correlated (Spearman correlation coefficient range, 0.67-0.96) (eFigure 1 in the Supplement). Moreover, the concentrations of PM₁ and PM_2.5 (Spearman correlation coefficient range, 0.48-0.87) and PM_2.5-10 and PM₁₀ (Spearman correlation coefficient range, 0.59-0.79) in different periods were moderately to highly correlated (eFigure 1 in the Supplement).

Exposure to PM₁, PM_2.5, and PM₁₀ in Early Life in Different Cities

Figure 1 shows the geographic location of the study cities and concentrations of PM₁, PM_2.5, and PM₁₀ in early life in different cities. Shanghai, a coastal city, had a median concentration of 35.0 μg/m³ (IQR, 32.9-37.9 μg/m³) for PM₁, 56.4 μg/m³ (IQR, 53.0-61.1 μg/m³) for PM_2.5, and 88.8 μg/m³ (IQR, 81.3-98.8 μg/m³) for PM₁₀, concentrations lower than in all inland cities except Urumqi. For inland cities, the lowest median concentration of PM₁₀ was found in Changsha (101.0 μg/m³ [IQR, 94.9-112.1 μg/m³]), and the lowest median concentrations of PM₁ and PM_2.5 were observed in Urumqi (15.8 μg/m³ [IQR, 14.4-17.5 μg/m³] and 42.3 μg/m³ [IQR, 35.9-51.0 μg/m³], respectively).

Early-Life Size-Segregated Particles Exposure and Childhood Asthma and Wheeze

Figure 2 shows the ORs and 95% CIs for the associations of early-life exposure to size-segregated particles with childhood asthma and wheeze. The estimates from model 1 (crude) to model 4 (adjusted for characteristics of children, parents, and household environments) were generally stable, indicating that the results of model 4, which included the most covariates, were robust. Each 10-μg/m³ increase in early-life PM₁ and PM_2.5 exposure was associated with an increase in the risk of childhood asthma by 55.0% (OR, 1.55; 95% CI, 1.27-1.89) and 14.0% (OR, 1.14; 95% CI, 1.03-1.26), respectively, whereas there was no association between early-life PM_1-2.5 exposure and childhood asthma. Similarly, there was a significant association between early-life PM₁₀ exposure and childhood asthma (OR, 1.11 [95% CI, 1.02-1.20] per 10-μg/m³ increase in PM₁₀), whereas there was no association between early-life PM_2.5-10 exposure and childhood asthma. As for childhood wheeze, we only identified associations with early-life PM₁ exposure (OR, 1.23 [95% CI, 1.07-1.41] per 10-μg/m³ increase in PM₁) and PM_2.5 exposure (OR, 1.08 [95% CI, 1.01-1.16] per 10-μg/m³ increase in PM_2.5); no associations were observed for other size-segregated particles.

Figure 3 provides the exposure-response relationships of exposure to size-segregated particles in early life with childhood asthma and wheeze. Significant upward linear relationships of early-life PM₁ exposure with risk of asthma and wheeze were observed. Early-life PM_2.5-10 and PM₁₀ exposure also showed upward linear relationships with the risk of asthma. Moreover, a significant nonlinear relationship of early-life PM_2.5 exposure with risk of asthma was observed. No other exposure-response relationships were identified between size-segregated PM exposure and risk of asthma and wheeze.

Prenatal and First-Year Size-Segregated Particles Exposure and Childhood Asthma and Wheeze

As presented in Figure 4, prenatal PM₁ exposure was positively associated with childhood asthma: for each 10-μg/m³ increase in exposure, the risk of childhood asthma increased by 29.0% (OR, 1.29; 95% CI, 1.12-1.50). Likewise, first-year PM₁ exposure was associated with increased risk of childhood asthma (OR, 1.52 [95% CI, 1.25-1.84] per 10-μg/m³ increase in PM₁). Compared with prenatal PM_2.5 and PM₁₀ exposure, estimates of the association of first-year PM_2.5 and PM₁₀ exposure with childhood asthma were similar (eg, OR, 1.10 [95% CI, 1.00-1.20] per 10-μg/m³ increase in first-year PM_2.5; OR, 1.09 [95% CI, 1.01-1.17] per 10-μg/m³ increase in prenatal PM_2.5). First-year PM₁ exposure was associated with greater risk of childhood wheeze than was prenatal PM₁ exposure (first-year PM₁: OR, 1.20 [95% CI, 1.05-1.37]; prenatal PM₁: OR, 1.14 [95% CI, 1.03-1.26]).

Sensitivity Analyses

Similar results were found in children born at term and children overall in associations of early-life exposure to size-segregated particles with childhood asthma and wheeze (eTable 2 in the Supplement). When controlling for PM_2.5 concentrations, the risk of childhood asthma increased by 4.0% (OR, 1.04; 95% CI, 1.02-1.05) and the risk of wheeze increased by 1.0% (OR, 1.01; 95% CI, 1.00-1.02) per 1% increase in the ratio of early-life PM₁ to PM_2.5 concentrations (eFigure 2 in the Supplement). No association was observed between the ratio of prenatal PM₁ to PM_2.5 concentrations and childhood wheeze, whereas the ratio of first-year PM₁ to PM_2.5 concentrations was significantly associated with childhood wheeze (OR, 1.01 [95% CI, 1.00-1.02] per 1% increase in the ratio of first-year PM₁ to PM_2.5 concentrations) (eFigure 2 in the Supplement).

We found that in the analyses of the associations of early-life PM₁ exposure with childhood asthma and wheeze, the results were comparable to the original results when the concentration of PM_1-2.5 was added to the model as a covariate (eTable 3 in the Supplement). The results of mutually adjusted analyses of associations of early-life PM_1-2.5, PM_2.5, and PM_2.5-10 exposure with childhood asthma and wheeze were also found to be consistent with the original results (eTable 3 in the Supplement).

Discussion

The results of this study indicated that early-life PM₁, PM_2.5, and PM₁₀ exposure were associated with childhood asthma in children aged 3 to 6 years in China, with higher estimates for PM₁ exposure. No association was observed for PM_1-2.5, suggesting that PM₁ rather than PM_1-2.5 contributed to the association between PM_2.5 and asthma. A significant upward linear exposure-response relationship was observed between early-life PM₁ exposure and risk of asthma. In addition, significant associations between early-life PM exposure and childhood wheeze were observed for PM₁ and PM_2.5. To our knowledge, this is the first multicity study in China to investigate long-term associations of early-life PM₁ exposure with childhood asthma and wheeze and to compare outcomes of PM₁ and PM_2.5 exposure by also assessing exposure to PM_1-2.5.

In the present study, early-life exposure to both PM₁ and PM_2.5 showed consistent results regarding associations with childhood asthma and wheeze. After the exclusion of children who had an asthma diagnosis but no report of wheeze, no associations were observed between early-life PM₁₀ exposure and either childhood asthma or wheeze (eTable 4 in the Supplement). The consistent results may indicate that wheeze could be one of the main factors associated with childhood asthma. Our findings are consistent with epidemiological studies of PM_2.5 and PM₁₀ exposure conducted in Canada^13,36 and the US^37,38,39 as well as in Shanghai,³² Wuhan,²² Changsha,³⁴ and Taichung City in China.³⁵ Nevertheless, discrepancies still exist across research. A study conducted in Changsha did not observe an association between prenatal PM₁₀ exposure and childhood asthma³³; a possible reason may be the difference in the exposure assessment methods because the researchers used the address of the kindergarten rather than the home address of the children. No association between PM_2.5 exposure and childhood asthma was found in 2 studies conducted in Canada.^40,41 The absence of an association might have been owed to the comparatively small concentration gradient of PM_2.5, with the median concentration of PM_2.5 in the studies being 10 μg/m³ and 4 μg/m³, respectively.

We identified statistically significant associations between early-life PM₁ exposure and elevated risk of both childhood asthma and wheeze, showing higher estimates than for PM_2.5 and PM₁₀. Mutually adjusted PM exposure models also showed results similar to separately included PM exposure models, demonstrating the robustness of our main results. Our results were generally consistent with those of a cross-sectional study conducted in 7 cities in northeast China that revealed associations between long-term PM₁ exposure and increased risk of asthma and wheeze and also found higher estimates with asthma.²¹ A previous single-city study conducted in Wuhan by some of us reported that prenatal rather than first-year PM₁ exposure was associated with increased risk of childhood asthma, and neither prenatal nor first-year PM₁ exposure was associated with childhood wheeze.²² The different findings between the previous study in Wuhan and the present study may be owed to the difference in the distribution of PM measures and asthma prevalence between study sites. The differences could also be attributed to the previous study²² estimating hazard ratios instead of ORs, as in the present study. Although the epidemiological evidence of an association between PM₁ and respiratory diseases is limited, PM₁ exposure in this study was associated with respiratory toxic effects. Therefore, more studies are urgently needed to explore the adverse effects of PM₁ on human health.

In this study, we found that the association between PM_2.5 and asthma was attributable more to PM₁ than to PM_1-2.5. The result of our sensitivity analyses with regard to the ratio of PM₁ to PM_2.5 concentrations also indicated that PM₁ contributed to the risk of childhood asthma and wheeze associated with PM_2.5. In a case-crossover study conducted in Shenzhen, an association with risk of hospitalization for respiratory disease was identified for short-term exposure to both PM₁ and PM_2.5, but not PM_1-2.5.⁴² Likewise, data from 26 Chinese cities indicated that the association of PM_2.5 exposure with emergency hospital visits was mostly due to PM₁.⁴³ Another study on PM-associated mortality elucidated that PM₁ accounted for most short-term PM_2.5-associated respiratory and chronic obstructive pulmonary disease mortality.⁴⁴ The underlying biological mechanism may be that PM with a smaller particle size, such as PM₁, is more likely to enter the deep respiratory tract and stimulate the alveolar wall, causing lung function impairment through oxidative stress and inflammation, and to further enter the blood circulation through the blood vessel walls.^19,45,46 Moreover, PM₁ has a larger active surface area, to which more toxic substances can attach.^47,48 In a recent study in Vietnam, Hien et al reported that long-range transport aerosols, coal fly ash, and primary particulate vehicular emissions mainly appeared in PM₁, whereas resuspended road dust and biomass-burning fly ash tended to occur in PM_1-2.5; these findings indicate a potential underlying mechanism by which PM₁ rather than PM_1-2.5 contributed to the association between PM_2.5 and asthma.⁴⁹ These findings may be of great importance to public health for ambient PM pollution control.

Strengths and Limitations

This study has strengths. First, an advantage of this study includes the advanced exposure assessment method using a machine learning technique. Estimates of high-resolution (1 × 1-km) spatiotemporal modeling are sufficient to accurately evaluate individual exposure. In addition, we considered a multitude of potential confounders in the adjusted models, including characteristics of children, parents, and household environments, which we believe allowed us to come to a robust conclusion.

Our study also has limitations. Due to the cross-sectional design of this study, we were unable to provide evidence of temporal and causal relationships between PM exposure and childhood respiratory outcomes. Moreover, ascertainment of childhood asthma and wheeze was acquired by self-reported questionnaires completed by caregivers and not validated by a physician; thus, they were susceptible to recall bias, and we could not determine in which direction this bias might have distorted the associations according to the present data. Most of the questionnaire respondents were mothers with university education or above, which may be due to our study selecting 7 provincial capitals in China, and this may have caused potential sampling bias. In addition, we were unable to analyze the associations of the sources and chemical composition of PM with childhood asthma and wheeze due to the lack of PM composition data. We also did not collect data on the number of wheeze episodes; thus, we were unable to further elucidate potential reasons for the inconsistent results regarding an association of PM₁₀ exposure with wheeze and asthma. In addition, although educational level is a recommended and typical indicator of socioeconomic status, we did not collect any other metrics that representatively indicate socioeconomic status, such as urbanization, family income, and maternal job title; thus, we could not include other indicators of socioeconomic status as covariates in the model for analyses. Furthermore, although we included indoor air pollution from solid fuel as a covariate and outdoor PM exposure and indoor PM exposure are correlated,^50,51 indoor PM exposure still differs among individuals. We may consider both indoor and outdoor PM concentrations as well as their chemical composition in future studies.

Conclusions

In this study, higher estimates were observed for the association between smaller-particle PM, such as PM₁, with childhood asthma than for PM with larger particles, suggesting that PM with a smaller particle size may be more toxic. In addition, PM₁ was a main contributor to the association between PM_2.5 and childhood asthma, suggesting that PM₁ may be more important than PM with larger particles. Efforts should be continued to carry out air purification actions, effectively control PM pollution, and develop air quality guidelines for PM₁ to reduce the adverse health impact of PMs, especially for children in China.

Supplement.

eMethods.

eTable 1. Distributions of Particulate Matter Concentrations in Early Life, During Pregnancy, and in the First Year of Life

eTable 2. Odds Ratios for the Association of Early-Life Exposure to Size-Segregated Particles With Childhood Asthma and Wheeze Among Term-Birth Children

eTable 3. Odds Ratios for the Associations of Early-Life, Prenatal, and First-Year Exposure to Size-Specific Particles With Childhood Asthma and Wheeze When Two-Pollutant Models Were Fitted

eTable 4. Odds Ratios for the Association of Early-Life Exposure to PM₁₀ With Childhood Asthma and Wheeze After Excluding Children Who Have an Asthma Diagnosis but no Report of Wheeze

eFigure 1. Spearman Correlation Coefficients Between Pairs of Size-Segregated PM Measures in Different Periods

eFigure 2. Odds Ratios for the Associations of the Ratio of Early-Life, Prenatal, and First-Year PM₁ to PM_2.5 With Childhood Asthma and Wheeze

Click here for additional data file.^{(603.9KB, pdf)}

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement.

eMethods.

eTable 1. Distributions of Particulate Matter Concentrations in Early Life, During Pregnancy, and in the First Year of Life

eTable 2. Odds Ratios for the Association of Early-Life Exposure to Size-Segregated Particles With Childhood Asthma and Wheeze Among Term-Birth Children

eTable 3. Odds Ratios for the Associations of Early-Life, Prenatal, and First-Year Exposure to Size-Specific Particles With Childhood Asthma and Wheeze When Two-Pollutant Models Were Fitted

eTable 4. Odds Ratios for the Association of Early-Life Exposure to PM₁₀ With Childhood Asthma and Wheeze After Excluding Children Who Have an Asthma Diagnosis but no Report of Wheeze

eFigure 1. Spearman Correlation Coefficients Between Pairs of Size-Segregated PM Measures in Different Periods

eFigure 2. Odds Ratios for the Associations of the Ratio of Early-Life, Prenatal, and First-Year PM₁ to PM_2.5 With Childhood Asthma and Wheeze

Click here for additional data file.^{(603.9KB, pdf)}

[zoi221017r1] 1.Stanaway JD, Afshin A, Gakidou E; GBD 2017 Risk Factor Collaborators . Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2018;392(10159):1923-1994. doi: 10.1016/S0140-6736(18)32225-6 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi221017r2] 2.Xie R, Sabel CE, Lu X, et al. Long-term trend and spatial pattern of PM_2.5 induced premature mortality in China. Environ Int. 2016;97:180-186. doi: 10.1016/j.envint.2016.09.003 [DOI] [PubMed] [Google Scholar]

[zoi221017r3] 3.Kim KH, Kabir E, Kabir S. A review on the human health impact of airborne particulate matter. Environ Int. 2015;74:136-143. doi: 10.1016/j.envint.2014.10.005 [DOI] [PubMed] [Google Scholar]

[zoi221017r4] 4.Kan H, Chen R, Tong S. Ambient air pollution, climate change, and population health in China. Environ Int. 2012;42:10-19. doi: 10.1016/j.envint.2011.03.003 [DOI] [PubMed] [Google Scholar]

[zoi221017r5] 5.Vos T, Lim SS, Abbafati C; 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. Lancet. 2020;396(10258):1204-1222. doi: 10.1016/S0140-6736(20)30925-9 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi221017r6] 6.Olsson D, Forsberg B, Bråbäck L, et al. Early childhood exposure to ambient air pollution is associated with increased risk of paediatric asthma: an administrative cohort study from Stockholm, Sweden. Environ Int. 2021;155:106667. doi: 10.1016/j.envint.2021.106667 [DOI] [PubMed] [Google Scholar]

[zoi221017r7] 7.Liu S, Jørgensen JT, Ljungman P, et al. Long-term exposure to low-level air pollution and incidence of asthma: the ELAPSE project. Eur Respir J. 2021;57(6):57. doi: 10.1183/13993003.030992020 [DOI] [PubMed] [Google Scholar]

[zoi221017r8] 8.Braman SS. The global burden of asthma. Chest. 2006;130(1)(suppl):4S-12S. doi: 10.1378/chest.130.1_suppl.4S [DOI] [PubMed] [Google Scholar]

[zoi221017r9] 9.National Asthma Education and Prevention Program . Expert Panel Report 3 (EPR-3): guidelines for the diagnosis and management of asthma—summary report 2007. J Allergy Clin Immunol. 2007;120(5)(suppl):S94-S138. doi: 10.1016/j.jaci.2007.09.029 [DOI] [PubMed] [Google Scholar]

[zoi221017r10] 10.Zar HJ, Ferkol TW. The global burden of respiratory disease—impact on child health. Pediatr Pulmonol. 2014;49(5):430-434. doi: 10.1002/ppul.23030 [DOI] [PubMed] [Google Scholar]

[zoi221017r11] 11.The Global Asthma Report 2018. Global Asthma Network; 2018. Accessed September 8, 2022. http://globalasthmareport.org/Global%20Asthma%20Report%202018.pdf

[zoi221017r12] 12.Yan W, Wang X, Dong T, et al. The impact of prenatal exposure to PM_2.5 on childhood asthma and wheezing: a meta-analysis of observational studies. Environ Sci Pollut Res Int. 2020;27(23):29280-29290. doi: 10.1007/s11356-020-09014-6 [DOI] [PubMed] [Google Scholar]

[zoi221017r13] 13.Clark NA, Demers PA, Karr CJ, et al. Effect of early life exposure to air pollution on development of childhood asthma. Environ Health Perspect. 2010;118(2):284-290. doi: 10.1289/ehp.0900916 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi221017r14] 14.Lasso-Pirot A, Delgado-Villalta S, Spanier AJ. Early childhood wheezers: identifying asthma in later life. J Asthma Allergy. 2015;8:63-73. [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi221017r15] 15.Burbank AJ, Sood AK, Kesic MJ, Peden DB, Hernandez ML. Environmental determinants of allergy and asthma in early life. J Allergy Clin Immunol. 2017;140(1):1-12. doi: 10.1016/j.jaci.2017.05.010 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi221017r16] 16.Chen G, Knibbs LD, Zhang W, et al. Estimating spatiotemporal distribution of PM₁ concentrations in China with satellite remote sensing, meteorology, and land use information. Environ Pollut. 2018;233:1086-1094. doi: 10.1016/j.envpol.2017.10.011 [DOI] [PubMed] [Google Scholar]

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PERMALINK

Associations of Early-Life Exposure to Submicron Particulate Matter With Childhood Asthma and Wheeze in China

Chuansha Wu, PhD

Yunquan Zhang, PhD

Jing Wei, PhD

Zhuohui Zhao, PhD

Dan Norbäck, PhD

Xin Zhang, PhD

Chan Lu, PhD

Wei Yu, PhD

Tingting Wang, PhD

Xiaohong Zheng, PhD

Ling Zhang, PhD

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Design, Setting, and Participants

Exposures

Main Outcomes and Measures

Results

Conclusions and Relevance

Introduction

Methods

Study Population

Exposure Assessment

Respiratory Health Outcomes

Covariates

Statistical Analysis

Results

Characteristics of Study Population

Table. Characteristics of Children, Parents, and Household Environment in the Study.

Concentrations and Correlations of PM

Exposure to PM1, PM2.5, and PM10 in Early Life in Different Cities

Figure 1. Location of Study Cities and Early-Life Exposure to Particulate Matter (PM) by City.

Early-Life Size-Segregated Particles Exposure and Childhood Asthma and Wheeze

Figure 2. Association of Early-Life Exposure to Size-Segregated Particulate Matter (PM) With Childhood Asthma and Wheeze.

Figure 3. Exposure-Response Associations of Exposure to Size-Segregated Particles in Early Life With Childhood Asthma and Wheeze.

Prenatal and First-Year Size-Segregated Particles Exposure and Childhood Asthma and Wheeze

Figure 4. Association of Prenatal and First-Year Particulate Matter (PM) Exposure With Childhood Asthma and Wheeze.

Sensitivity Analyses

Discussion

Strengths and Limitations

Conclusions

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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Links to NCBI Databases

Exposure to PM₁, PM_2.5, and PM₁₀ in Early Life in Different Cities