Covariates and mediator
Information on covariates was obtained from the questionnaire, including
age (<5 years, 5-10 years, 10-15 years and ≥15 years), gender
(boy/girl), exercise time (hours/week), family income per year
(<10,000RMB, 10,000-29,999RMB, 30,000-99,999RMB, or
≥100,000RMB), parental education (≥high school or lower), low birth
weight (birth weight <2500g), premature birth (gestational age
<37), breastfeeding (child being mainly breastfed for at least
three months), obesity (yes/no), passive smoke exposure (child living
with someone of the household who smokes daily at residence), home coal
use (yes/no) and pet kept (yes/no), particulate matter with aerodynamic
diameters < 2.5 µm (PM2.5) exposure
(<48.97µg/m3,
48.97-56.23µg/m3, 56.23-60.57µg/m3,
or ≥60.57 µg/m3). The assessment of personal
PM2.5 exposure has previously been described in
detail.15,16 In brief, the average
PM2.5 concentration during 2009-2012, estimated
according to each participant’s residence using a machine learning
method, was regarded as a surrogate of individual exposure. Participants
were categorized into four groups based on quartiles of
PM2.5 concentration they were exposed. A directed
acyclic graph (DAG) was drawn by online DAGitty
(http://dagitty.net/dags.html)
(Fig. S1). Variables, containing passive smoke exposure, home coal use,
pet kept and PM2.5 exposure, were identified as
potential confounders that needed adjusting in the main model. In
addition, parent with asthma was identified as a potential mediator.