Methods
Study population
The Tasmanian Longitudinal Health study (TAHS) is a population-based
prospective cohort study, that has followed participants since 1968 when
7-year-old children (98.7%, n=8583) attending schools in the Australian
state of Tasmania were recruited.10 Several follow-up
surveys have subsequently been conducted and study methodology has been
reported in detail elsewhere.10 The data for this
analysis came from participants of the 2002 and 2012 proband studies
when participants were 43 and 53 years old respectively. Participants
completed a self-administered postal survey that collected the following
baseline (2002) and follow-up (2012) data: sociodemographic
characteristics, occupation, residence, health service use, medical
diagnoses, smoking, reproductive histories, and symptoms. Only
participants who completed both assessments and had valid skin prick
tests (performed at the 2012 follow-up) were included in the analysis.
The study was approved by the Human Research Ethics Committee of the
University of Melbourne; all participants provided written informed
consent.
Exposures
Distance to a major road
(DMR)
Straight-line distances from each participant’s residence to the nearest
major road in 2002 and 2012 proband studies were calculated using ArcGIS
10.1 software (Redlands, CA). Major roads were defined using public
sector mapping agencies, and Australian transport hierarchy codes 301
and 302.11 Participants were categorized into two
groups: (i) living <200m; or (ii) living ≥200m from a major
road. Major traffic pollutant concentrations tend to decay as the
distance to major roads (DMR) increases, with most components of TRAP
reaching near background concentrations at approximately
200m.12
Nitrogen dioxide
(NO2)
A satellite-based land-use regression model was used to assign mean
annual NO2 exposures for the 2002 and 2012 proband
studies.13 Briefly, the land-use regression
model-predicted mean annual NO2 levels were based on
tropospheric NO2 columns derived from satellite
observations in combination with other predictors such as land use and
roads, to estimate ground-level NO2 across
Australia.13 As more than half of the ambient
NO2 is attributed to on-road sources,
NO2 is a reasonable proxy for TRAP.14The model’s development and validation are described in detail
elsewhere, and it explained 81% of spatial variability in measured
annual NO2 at all regulatory monitoring sites in Australia.13 Mean annual residential exposures to outdoor
NO2 were estimated and assigned based on participants’
geocoded addresses at baseline (2002 proband study) and follow-up (2012
proband study).
Fine particulate matter with an
aerodynamic diameter <2.5 µm
(PM2.5)
The methods are explained in more detail elsewhere.15In brief, satellite-based estimates for Australia of ground-level
PM2.5 were used as a land-use regression predictor, with
other spatial predictors of PM2.5 . This model explained
63% of spatial variability in measured annual PM2.5(RMSE: 1 µg/m3).15 The mean annual
residential exposures to outdoor PM2.5 were estimated
and assigned based on participants’ geocoded addresses at baseline and
follow-up. In Australia, traffic-related sources of
PM2.5 are estimated to account for only 17% of ambient
PM2.5 mass, while the majority of ambient
PM2.5 is from other anthropogenic sources (i.e. wood
heaters, power stations and non-road combustion).16
Outcomes
Prevalent eczema at 53 years
Prevalent eczema at age 53 (2012 proband study) was determined using the
International Study of Asthma and Allergies in Childhood (ISAAC)
definition of eczema.17 Participants were classified
as having prevalent eczema if they reported “yes” to all three
questions: ‘have you had an itchy rash in the past 12 months?’, ‘Have
you ever had an itchy rash coming and going for at least six months?’,
and ‘Has this itchy rash at any time affected any of the following
places: the folds of the elbows, behind the knees, in front of the
ankles, under the buttocks, or around the neck, ears or eyes?’
Incident current eczema at 53 years
Incident current eczema at 53 years was defined as eczema newly arising
between the two proband studies i.e. between 43 and 53 years. The
participants were classified as having Incident eczema if they answered
“no” to “Have you ever had eczema or any skin allergy?” at baseline
(2002 proband study), but reported eczema based on the ISAAC
definition17 and having eczema for the first time
after baseline at “How old were you when you first had this itchy
rash?” at the follow-up (2012 proband study.
Persistent current
eczema
Persistent current eczema was defined as prevalent eczema at baseline
that persisted to follow-up. Participants were classified as having
persistent current eczema if they answered “yes” to “Have you ever
had eczema or any skin allergy?” at baseline and reported eczema based
on the ISAAC definition17 at follow-up.
Atopic status
Subclassification as AE or NAE was based on skin prick testing (SPT)
results at age 53 years. 10 In the 2012 proband study,
SPTs were performed for eight aeroallergens: Dermatophagoides
pteronyssinus , cat pelt, Cladosporioides , Alternaria
tenuis , Penicillium mix, Aspergillus fumigatus , mixed
grass pollen No. 7 (which included Kentucky bluegrass, orchard, redtop,
Timothy, sweet vernal grass, meadow fescue and perennial ryegrass).
Histamine was used as the positive control and normal saline as the
negative control. After 10 to 15 mins, the wheal diameters were measured
in two perpendicular directions in millimetres and an average was
derived. A valid SPT was determined by a positive control or allergen
wheal equal to or greater than 3 mm in size and a negative control wheal
equal to or less than 3 mm in size. A positive SPT was defined as a
wheal size of at least 3 mm greater than the negative control and was
considered to indicate sensitisation to that
allergen.18 Atopy was defined as sensitization to at
least one of the allergens tested.
Statistical Analysis
Associations between markers of ambient air pollution and the following
outcome measures were assessed: 1) Prevalent eczema, 2) Incident current
eczema, 3) Persistent eczema, 4) Prevalent and incident eczema sub
grouped by atopic status (neither, atopy alone, non-atopic and atopic
eczema) and 5) Sensitisation (regardless of eczema status). Second, in
accordance with the eczema and atopy classification used in the SALIA
cohort study 6, we examined NAE incidence and
prevalence using three increasingly restricted subgroups: 1) all
participants, 2) participants without hay fever ever, 3) participants
without hay fever ever and negative SPT.
Logistic regression and multinomial models were fitted to estimate the
associations between baseline ambient air pollution and each outcome.
The coefficients represented the estimated effect per interquartile
range (IQR) increase of air pollutant exposure and were expressed as
odds ratios (ORs) with 95% confidence intervals (CIs). A directed
acyclic graph (DAG) (supplementary figure 1) was developed to specify
the hypothesized causal relationships and to determine which confounders
to include in the model (supplementary table 1). The potential presence
of non-linearity of these associations was assessed using Stata’s
“fracpoly” command; no evidence of non-linearity of associations
between ambient air pollution markers and eczema was identified.
Potential effect modification by sex was explored using likelihood ratio
tests and a p value < 0.1 was considered as significant. A
sensitivity analysis was performed, where associations were assessed
only in the participants who did not change residential address during
follow-up period. All analyses were carried out using the statistical
software Stata (release 16; Stata Corporation, College Station, TX).