Journal of Environmental Protection, 2013, 4, 779-788
http://dx.doi.org/10.4236/jep.2013.48091 Published Online August 2013 (http://www.scirp.org/journal/jep)
779
Childhood Exposure to Air Pollution as a P otential
Contributor of Chronic Non-Respiratory Inflammatory
Disorders: A Longitudinal Prospective Cohort Study in
Hamilton, Canada
Caroline Barakat-Haddad1*, Susan Elliott2, David Pengelly3
1Department of Anthropology, University of Toronto Scarborough, Toronto, Canada; 2Faculty of Applied Health Sciences, Univer-
sity of Waterloo, Waterloo, Canada; 3Department of Medicine, McMaster University, Hamilton, Canada.
Email: *cbarakat@utsc.utoronto.ca, elliotts@uwaterloo.ca, Pengelly@mcmaster.ca
Received May 13th, 2013; revised June 15th, 2013; accepted July 20th, 2013
Copyright © 2013 Caroline Barakat-Haddad et al. This is an open access article distributed under the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
ABSTRACT
This study examines the relationship between childhood exposure to air pollution and diagnosis with chronic non-re-
spiratory health outcomes in adulthood. This prospective cohort study uses data collected in the 1970/1980s from 395
children, including exposure to air pollution. Over thirty years later, a survey collected data on various health outcomes,
including diagnosis with arthritis, high blood pressure, long-term skin conditions, and hay fever allergies. Logistic re-
gression modeling was performed to examine the relative contribution of childhood exposure to air pollution on chronic
non-respiratory health outcomes in adulthood. Childhood exposure to SO2 emerged as a significant predictor of arthritis
(OR = 2.73, 95% CI 1.20 - 6.18) and high blood pressure (OR = 2.82, 95% CI 1.23 - 6.47). Other significant predictors
include respiratory symptoms during childhood, family income during childhood and adulthood, property tenure, em-
ployment status, residential exposures, life events, physical activity, and body mass index. Childhood exposure to air
pollution did not emerge as a significant predictor of long-term skin conditions or hay fever allergies. Findings contrib-
ute to the debate on the health effects of air pollution, indicating that the health impacts of childhood exposure to air
pollution may include chronic inflammatory disorders in adulthood.
Keywords: Air Pollution; Health Development; Hay Fever; Arthritis; Hypertension; Skin Diseases
1. Introduction
Exposure to air pollution is detrimental to health. Litera-
ture documents increased risks of morbidity and mortal-
ity from exposure to acute episodes of air pollution [1].
For example, the London fog of 1952 led to an estimated
12,000 additional attributable deaths over a period of
several months following the high levels of air pollution
[1]. Policies adopted since the mid-twentieth century and
largely driven by the environmental movement have re-
duced the levels of visible air pollutants [2]. While acute
episodes of ambient air pollution have decreased, chronic
exposures to relatively lower levels of air pollution are
also implicated with negative health outcomes. Much of
the air pollution and health research focuses on vulner-
able sub-populations, who may be most impacted by
these exposures. Children are a sensitive sub-population
due to their relatively smaller lungs, their stage of devel-
opment and growth, and the proportion of time they
spend outdoors [3]. In addition to physiological and be-
havioral features, children’s relatively longer life expec-
tancy provides an opportunity for certain latent condi-
tions or diseases to manifest at some point along the life
course. Cohort studies on children are considered the
“gold standard” for assessing the long-term health im-
pacts of exposure to ambient air pollution.
We undertook a systematic review of studies published
between 1996 and 2006 on the relationship between
childhood exposure to air pollution—particulate matter
of any fraction size (PM), and sulphur dioxide (SO2)—
and health, which revealed 5 review studies and 26 geo-
graphically based cohort studies. The follow-up period of
these studies ranges between few weeks and 10 years,
*Corresponding author.
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Childhood Exposure to Air Pollution as a Potential Contributor of Chronic Non-Respiratory Inflammatory Disorders: A
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thus focusing on health measures in childhood. Studies
reported associations between exposure to particulate
matter of different sizes and bronchitis, lung function,
and respiratory morbidity [4-8]. Literature suggests that
PM2.5 have stronger acute respiratory impacts than
coarse particles [9] and that PM2.5 are associated with
decrements in lung function growth [10]. Significant
associations were also found between childhood expo-
sure to SO2 and respiratory symptoms (persistent wheeze,
cough, phlegm), lifetime prevalence of diagnosed asthma,
infectious airway diseases (such as pneumonia, bronchi-
tis, chest colds, and tonsillitis), and a decrease in lung
function [5,11-13].
While most findings suggest that childhood exposure
to chronic air pollution impacts respiratory health, there
is a gap in knowledge on its impacts (if any) on chronic
non-respiratory health outcomes in adulthood. This is
especially relevant given research evidence that ultrafine
PM can penetrate the epithelium and vascular walls in
the body and be transported via the circulatory system to
other body organs, where it can lead to inflammatory
events [14,15]. This may include the release of inflame-
matory mediators into the circulation, which stimulate
the bone marrow to release leukocytes and platelets, the
driving force of autoimmune diseases [16]. Ambient
pollutants trigger the respiratory tract epithelium to pro-
duce and release inflammatory cytokines [17] and can
also cause oxidative stress to other body cells leading to
inflammation [18,19]. Indeed, studies report positive
associations between PM exposures and brain markers of
inflammation in mice [20] and canines [21]. Human
studies suggest that exposure to air pollution is related to
brain inflammation and Abeta42 accumulation [22]. In-
halation of fine and ultrafine particles may also be related
to platelet activation, a contributory factor of blood co-
agulation reactions [23]. While many human studies have
in the past examined the link between exposure to air
pollution and non-respiratory health outcomes (such as
mortality and heart disease), these studies tend to focus
on the adult population and thus do not account for
childhood exposures to air pollution. Given that studies
provide compelling evidence that PM is linked to lung
and systemic inflammation [24,25], the possible link
between childhood exposure to ambient air pollution and
inflammatory disorders has yet to be fully explored [26].
There is scarce evidence that childhood exposure to air
pollution may be related to negative health impacts re-
lated to inflammation in children. For example, Kaplan et
al. [27] found that exposures to SO2 and NO2 in child-
hood may increase the risk of early-onset ulcerative coli-
tis and Crohn’s disease. Iannuzzi et al. [28] found that
exposure to air pollution is associated with early athero-
sclerotic markers in healthy children. Poursafa et al. [29]
found a positive association between childhood exposure
to PM10 and the expression of tissue factor (TF) in
atherosclerotic lesions, a key initiator of coagulation and
considered to have a pivotal role in atherothrombosis.
When accounting for the possible role of genetic varia-
tions in TF, a follow-up study suggests that in spite of
similar genetic background, exposure to air pollutants
had an independent association with serum TF level [30].
Associations have also been reported between exposure
to air pollution and neurodevelopment and neurobehav-
ioral functions in both children and adults [31-33], and
the prevalence of anemia in children [34]. More recently,
a review on the link between air pollution and non-al-
coholic fatty liver diseases (NAFLD) documents evi-
dence that point to air pollutant-induced systemic pro-
inflammatory and oxidative responses as a risk factor for
NAFLD [35]. The review points to results of a popu-
lation-based study of children that found independent
associations between different markers of air pollutants
(including PM10 and SO2) and plasma markers of in-
flammation, oxidative stress, and insulin resistance [36].
The main objective of this study is to examine whether
childhood exposures to ambient air pollutants are pre-
dictors of adult non-respiratory health outcomes: mainly,
arthritis, high blood pressure, long-term skin conditions,
and hay fever or allergies.
2. Methods
This prospective cohort study uses as a foundation 30-
year old longitudinal exposure and health outcome data
from a cohort of participants (n = 3202) who resided in 4
distinct neighborhoods in Hamilton Ontario between
1978 and 1986 (Figure 1). The selected geographically
distinct neighborhoods exhibited a gradient in air pollu-
tion levels with the east lower neighborhood having the
highest levels of air pollution compared to the other three
neighborhoods. Participants were between 6 and 8 years
old in 1978. Data on air pollutant levelsSO 2 and
particulate matterwas collected using a network of 22
monitoring stations located throughout the City of Hami-
lton. At the time, the cut-off size for measuring exposure
to fine particulate was not recognized, and fine particu-
late was measured using PM under 3.3 µm in aerodyna-
mic diameter (PM3.3). (The current cut-off is PM2.5). In
2006, all cohort members who were successfully located
(n = 929) were invited to participate in this study; 68%
consented to participate (n = 598). A survey was deve-
loped for this research and was approved by the McMas-
ter University Research Ethics Board (MREB). Data
from childhood was obtained from the original research,
while data from adulthood was collected using the self-
administered survey. Follow-up postcards and telephone
reminders were used to enhance response rates, resulting
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Childhood Exposure to Air Pollution as a Potential Contributor of Chronic Non-Respiratory Inflammatory Disorders: A
Longitudinal Prospective Cohort Study in Hamilton, Canada
781
Figure 1. Map of the study area.
in a response rate of 66%. Details of the original research
program, research findings, cohort tracing, and results
related to respiratory health outcomes have been publish-
ed in this journal and elsewhere [37-42].
2.1. Independent Variables from Childhood
2.1.1. Exposure Assessment
Data on childhood exposure to air pollution included
levels of SO2 in 1978/9 (mean age of participants = 8
years); 1980/1 (mean age = 9 years), 1981/2 (mean age =
10), and 1983/4 (mean age = 13 years); TSP in 1980/1,
1983/4, and 1985/6 (mean age = 15 years); and PM3.3 in
1980/1, 1981/2, 83/4, and 1985/6. There were four me-
thods that derived variables related to childhood expo-
sure to air pollution for inclusion in the analysis. First,
given that each participant was assigned personal annual
exposure values in childhood—to TSP and PM3.3 in
1980/1, 1981/2, 1983/4, and 1985/6; and exposures to
SO2 in 1978/9, 1980/1, 1981/2, and 1983/4—based on
estimates derived from a response surface model [41],
exposure to air pollution was retained as a continuous
variable. In addition, exposure data were used to group
participants into two categories based on whether they
were exposed to specific air pollutants above the me-
dian level or at/below the median level for each sampling
period (academic year)—a common method of evaluat-
ing exposures in air pollution epidemiology. The third
method consisted of creating indices that indicate the
frequency of exposure to TSP, PM 3.3 and SO2 above or
below the median level across all sampling periods.
Lastly, participants were also categorized according to
their residence in childhood into four geographic neigh-
borhoods.
2.1.2. Additiona l Independen t V ar iables
Other variables from childhood include exposure to sec-
ond-hand smoking, household income (below the low-
income cut-off versus at or above the low income cut-
off), dwelling type, smoking experience (one or more
cigarettes per day for more than 6 months), age when
smoking started, and asthma diagnosis. In order to ex-
amine the relative contribution of indoor air quality in
childhood on long-term respiratory health, this environ-
mental aspect was assessed using variables that measured
exposure to indoor versus outdoor air including such as
gas cooking. In addition, indices representing respiratory
health in childhood were created for persistent morning
cough, persistent day/night cough, persistent wheeze,
chest colds or illnesses, and airway obstruction. The lat-
ter is assessed using the FEV1/FVC indicator (ratio of
the forced expiratory volume in one second over the
forced vital capacity) at or below the median. This meas-
ure was selected because it is intrinsically independent of
body size [39].
2.2. Independent Variables from Adulthood
Independent variables from adulthood (mean age of
participants = 36 years) include data on the participant’s
macro-environment. This includes variables related to the
residential environment, occupational history and expo-
sures, socio-demographic variables, healthcare access,
and life events. Data on the participant’s microenviron-
ment relates to behavioral (smoking, alcohol consump-
tion, and physical activity), psychological (concern over
air pollution; emotional distress; and feelings about in-
come, health, and life) [43], and physiological variables
(body mass index). Barakat-Haddad et al. (2012) [37]
includes a detailed description of collected and derived
variables from adulthood that are included in this analy-
sis.
2.3. Health Outcome Data
Non-respiratory health outcomes were measured using 6
questions that asked whether participants were ever dia-
gnosed with hay fever or environmental allergies, ar-
thritis or rheumatism, high blood pressure or hyper-
tension, any long-term skin conditions, any type of can-
cer, and any form of heart disease. Participants were also
asked questions related to their respiratory health. Health
measures are included as binary variables in the analysis.
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Childhood Exposure to Air Pollution as a Potential Contributor of Chronic Non-Respiratory Inflammatory Disorders: A
Longitudinal Prospective Cohort Study in Hamilton, Canada
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2.4. Statistical Analyses
Analysis was performed using the Statistical Package for
the Social Science (SPSS-v12). A series of logistic
regression modeling were run in order to examine the re-
lative contribution of independent variables in predicting
the occurrence of the following health outcomes: arth-
ritis, hypertension, long-term skin conditions, hay fever
or allergies, cancer, and heart disease. The method used
in deriving these models is detailed in Barakat-Haddad et
al. (2012) [37]. Results consist of two models for each
health outcome one that includes significant predictors
that explain the health outcome (best-fit model) and one
that assesses the relative role of long-term exposure to air
pollution on each health outcome, which is obtained by
including the indices of long-term exposure to air pollu-
tion in the best fit models. The specificity and sensitivity
of the models were noted.
3. Results
The prevalence of variables from the macro- and micro-
environments are summarized in Table 1. The prevalence
of the examined health outcomes is not significantly dif-
ferent across the four geographical neighborhoods (Table
2). In the first model, we examine diagnosis with arthritis
or rheumatism. Results suggest that this health outcome is
predicted by exposure to SO2 above the median level of
11.7 ppb in 1983/84 (mean age of participants = 13 years),
experiencing two or more stressful life events, residential
exposure to dust/gas/contaminants for a duration that ex-
ceeds 5 years, and being below the low-income cut-off in
childhood (Table 3). Predictors of arthritis or rheuma-
tism change when data are disaggregated by sex. The
rho-square values for sex-specific models are greater than
0.2 indicating a good fit. However, the large range of
confidence intervals for variables such as index for cough
in childhood indicates uncertainty regarding the true ef-
fect of the explanatory variable. When variables related to
long-term exposure to air pollution and neighborhood of
residence in childhood are included in the best-fit model
for arthritis or rheumatism, exposure to SO2 above 11.7
ppb in 1983/84 is no longer a statistically significant pre-
dictor of diagnosis with arthritis or rheumatism (Table 4).
Surprisingly, results suggest that long-term exposure to
PM3.3 decreases the odds of arthritis/rheumatism for fe-
males.
Results suggest that diagnosis with high blood pressure
or hypertension is predicted by exposure to SO2 above
11.7ppb in 1983/84, property ownership, and a current
family income below the low-income cut-off (Table 3).
Although, gender-related analysis gives rise to different
predictors, rho-square values of all models are below 0.2
indicating a low goodness of fit (Table 3). When vari-
ables related to long-term exposure to air pollution and
neighborhood of residence in childhood are forced into
the best-fit model, exposure to SO2 above 11.7 ppb in
1983/84 remains a significant predictor of diagnosis with
high blood pressure/hypertension (Table 5). Possibly due
to the fact that some of the evaluated non-respiratory
health outcomes—such as cancer and heart disease—are
more typically seen in older adult populations, this re-
search did not have the ability to evaluate these health
outcomes. Childhood exposure to air pollution did not
emerge as a significant predictor of long-term skin condi-
tions, hay fever or allergies.
4. Discussion
The purpose of this article was to contribute to our un-
derstanding of the relative contribution of childhood ex-
posure to air pollution on adult non-respiratory health
outcomes. A number of issues arise from results of the
logistic regression models, which achieved a range of
values related to goodness of fit (rho-square value be-
tween 0.11 and 0.22), indicating good to strong goodness
of fit. While results suggest that location of residence in
childhood is not a predictor of diagnosis with arthritis or
high blood pressure, rho-square values increased in most
cases and remained the same in a few cases, when the
indices of air pollution and neighborhood of residence in
childhood were added to the models. This suggests that
there may be factors at the regional level that impact
these heath outcomes and that were not captured in the
analysis. Examples are factors that may be related to in-
equity in opportunities and resource distribution (air
quality), such as the degree of community integration,
and the effect of perceived areas on the self-esteem and
morale of residents.
Second, results suggest that exposure to SO2 in
1983/1984 above 11.7 ppb (when the mean age of par-
ticipants was 13 years) may predict arthritis/rheumatism
and high blood pressure/hypertension in adulthood.
Moreover, while accounting for the role of long-term
exposures to air pollution and area of residence, analysis
suggests that exposure to SO2 above 11.7ppb is a pre-
dictor of diagnosis with high blood pressure hypertension.
These findings deserve further investigation given re-
search evidence that implicates air pollution with sys-
temic inflammatory events [16,18,19,22] and the possible
onset or progression of inflammatory disorders [26], par-
ticularly early atherosclerotic markers in healthy children.
[28] While evidence about biological mechanisms im-
plicating air pollution with a range of body reactions—
such as platelet activation, oxidative stress, pro-inflam-
matory responses, expression of tissue factor, and insulin
resistance [14,15,17-19,23,26,29,30,35,36]- continues to
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Childhood Exposure to Air Pollution as a Potential Contributor of Chronic Non-Respiratory Inflammatory Disorders: A
Longitudinal Prospective Cohort Study in Hamilton, Canada
Copyright © 2013 SciRes. JEP
783
Table 1. Distribution of variables that are used in this study.
Construct Variables Classification %
Data from childhood ( 19 7 6-1986)
TSP (1980/1, 83/4, 85/6) (µg/m3)
TSP index
Range—annual averages
Medians
Always > median
31 - 75
51, 50, 46
17
PM3.3 (1980/1, 81/2, 83/4, 85/6) (µg/m3)
PM3.3 index
Range—annual averages
Medians
Always > median
34 - 69
46, 46, 52, 43
24
Exposure to air pollution
SO2 (1978/9, 1980/1, 81/2, 83/4) (ppb)
SO2index
Range—annual averages
Medians
Always > median
5.4 - 17.3
6.8, 10.6, 9.7, 11.7
10
Residential history Exposure to smoking
Neighborhood of residence
Exposed
WU, EU, WL, EL
55
29, 27, 19, 25
Cooking method Gas 22
Demographic features Sex
Household income
Male
Below low-income cut-off
49
16
Behavioral Smoking 1 per day for >6 months 16
Physiological factors
Asthma
Indices for persistent cough or wheeze
Chest colds/illness before age of 2
FEV1/FVC pulmonary index
Asthmatic
Range
Bronchitis/pneumonia
Range
11
0 - 1
6
>0 - 1
Data from adulthood (2006/2007)
Air quality Exposure to smoking Exposed 44
Residential history
Previous residences
Residential exposures to gas/dust/contaminants
Use of air conditioner, humidifier, filter
Type of heating
Air duct cleaning
Cooking method
Resided in property built before 1950
Always in Hamilton
Ever
(greater than 2, 5, 8 years)
Always/almost always
Gas/oil
Rarely/do not remember
Gas
>5 years
60
92
65, 57, 46
76, 29, 27
96
68
38
25
Occupational history
Employment status
Type of occupation
Length of occupational exposures to
gas/dust/contaminants (months)
Full-time
Clerical
Manual
Managerial
Professional
Ever
(greater than 2, 5, 8 years)
60
11
23
14
48
92
65, 57, 46
Healthcare system Healthcare Have family doctor, Private insurance 92, 70
Social environment Social contact scale*
Group participation scale*
Score 5
Score 4
12
69
Family environment Record of asthma/respiratory problems At least one parent 69
Marital status Married/common law 74
Demographic features
Education
Current family income
Ethnicity
Housing tenure
Completed high school
Below low-income cut-off
Born in Canada
Property ownership
98
5
95
85
Life events Life events 2 or more stressful events 10
Behavioral factors
Smoking
Alcohol
Physical exercise
Current smoker; ever daily smoker
Regular consumption
3 per week, >30 minutes
21, 34
11
49
Psychological factors
Concern over air pollution
Emotional distress
Feelings about income, health, life
Moderate/extreme
score 4 on GHQ
Mostly dissatisfied/unhappy/terrible
54
11
13, 7, 3
Physiological factors BMI 25 67
Childhood Exposure to Air Pollution as a Potential Contributor of Chronic Non-Respiratory Inflammatory Disorders: A
Longitudinal Prospective Cohort Study in Hamilton, Canada
784
Table 2. Prevalence of non-respiratory and respiratory medical diagnosis in the sample (n = 395).
Outcome (%) WU EU WL EL Total
Arthritis/rheumatism 11 9 9 12 10
High blood pressure/hypertension 7 11 13 9 10
Long-term skin conditions 13 17 13 22 17
Hay fever/allergies 43 48 40 37 42
Heart disease 0 2 3 0 1
Non-respiratory
Cancer 0 1 1 3 1
Respiratory problems 3 7 3 5 5
Asthma in adulthood 16 10 11 15 13
Chronic bronchitis 3 8 5 7 6
Chest conditions (pneumonia/lung infections) 3 6 7 6 5
Respiratory
Hospital/ER visits for respiratory problems since leaving elementary
school* 2 11 9 15 9
*p < 0.05; WU—west upper; EU—east upper; WL—west lower; EL—east lower.
Table 3. Logistic regression models for arthritis and high blood pressure.
Total (n = 327, 286) Females (n = 184, 184) Males (n = 191, 189)
Health
outcome Reference Group Classification OR 95.0% CI OR 95.0% CI OR 95.0% CI
Residential exposure to
dust/gas/contaminants for
5 years
Exposed for >5
years 4.57*** (2.07 to 10.11)7.24*** (2.42 to 21.67) 5.13* (1.36, 19.28)
Stressful life events (<2) 2 or more 3.67* (1.33 to 10.12) 8.27** (1.88, 36.32)
Exposure to SO2 (1983/84)
(11.7 ppb) >11.7 ppb 2.73* (1.20 to 6.18)
Family income in childhood
(>low income cut-off)
<low income
cut-off 3.84**(1.60 to 9.25) 5.35* (1.26, 22.68)
Physical activity (Not regular) >30 minutes/>3
days 4.24** (1.47 to 12.19)
Current family income
(>low income cut-off)
<low income
cut-off 5.57* (1.21 to 25.71)
Air conditioner (Do not own) Own 7.24** (1.95 to 26.95)
Index for cough in childhood
(Not persistent)
Persistent
day/night cough 167.73* (3.07, 9155.75)
Specificity (%) 76.7 73.5 66.9
Sensitivity (%) 58.8 66.7 84.6
Arthritis
Rho-square 0.16 0.22 0.20
Property (Do not own) Own 3.39** (1.44, 7.98) 5.25** (1.80 - 15.35)
Current family income
(>low income cut-off)
<low income
cut-off 4.01* (1.26, 12.74)
Exposure to SO2 (1983/84)
(11.7 ppb) >11.7 ppb 2.82* (1.23, 6.47)
Body mass index (<25) 25 4.03* (1.09 - 14.92)
Feelings about income
(Score 3) Score < 3 4.21* (1.36 - 13.04)
Employment(Not full-time) Full-time 4.07* (1.18 - 13.99)
Specificity (%) 46.1 47.6 79.1
Sensitivity (%) 87.1 84.2 64.7
High blood
pressure
Rho-square 0.11 0.12 0.12
*p < 0.05; **p < 0.01; ***p < 0.001.
Copyright © 2013 SciRes. JEP
Childhood Exposure to Air Pollution as a Potential Contributor of Chronic Non-Respiratory Inflammatory Disorders: A
Longitudinal Prospective Cohort Study in Hamilton, Canada
785
Table 4. Long-term exposure to air pollution in childhood and diagnosis with arthritis.
Overall sample (n = 327)Females (n = 184) Males (n = 201)
Reference Group Classification OR 95.0% CI OR 95.0% CI OR 95.0% CI
Residential exposure to dust/gas/
contaminants (5 years) >5 years 5.14*** (2.25, 11.73)7.84*** (2.59, 23.74) 4.82* (1.33, 17.44)
Stressful life events (<2) 2 or more 4.20** (1.49, 11.88) 5.25* (1.27, 21.70)
Exposure to SO2 (1983/84) (11.7 ppb) >11.7 ppb 3.01 (0.90, 10.04)
Family income in childhood
(>low income cut-off)
<low income
cut-off 3.98** (1.63, 9.68) 3.43 (0.89, 13.25)
Physical activity (Not regular) >30 minutes
/3 days 3.32* (1.20, 9.20)
Current family income
(>low income cut-off)
<low income
cut-off 4.45* (1.08, 18.40)
Air conditioner (Own) Do not own 6.79** (1.82, 25.41)
Index for cough in childhood
(Not persistent)
Persistent day/
night cough 146.74* (2.36, 9117.50)
Residence in childhood (West upper)
East lower 0.79 (0.25, 2.52) 0.84 (0.17, 4.30) 0.85 (0.16, 4.72)
West lower 0.46 (0.10, 2.12) 1.17 (0.21, 6.56) 0.39 (0.05, 2.97)
East upper 0.45 (0.13, 1.56) 0.31 (0.08, 1.28) 0.77 (0.08, 7.26)
Index for TSP exposure (median) >median 2.27 (0.47, 11.00)4.76 (0.74, 30.71) 0.41 (0.03, 5.53)
Index for PM3.3 exposure (median) >median 0.54 (0.06, 4.84) 0.04* (0.00, 0.53) 9.81 (0.31, 307.78)
Index for SO2 exposure (median) >median 1.04 (0.09, 11.93)7.80 (0.75, 80.66) 1.99 (0.16, 24.72)
Specificity (%) 74.1 71.8 76.8
Sensitivity (%) 58.8 68.0 75.0
Rho-square 0.18 0.22 0.21
*p < 0.05; **p < 0.01; ***p < 0.001.
Table 5. Long-term exposure to air pollution in childhood and high blood pressure.
Overall sample (n = 327)Females (n = 184) Males (n = 199)
Reference Group Classification OR 95.0% CI OR 95.0% CI OR 95.0% CI
Property ownership (Own) Do not own 3.52** (1.49, 8.30) 6.17** (2.01, 18.89)
Current family income
(>low income cut-off)
<low income
cut-off 3.45* (1.12, 10.69)
Exposure to SO2 (1983/84) (11.7 ppb) >11.7 ppb 4.24* (1.19, 15.09)
Body mass index (<25) 25 4.02* (1.09, 14.84)
Feelings about income
(Score 3) Score < 3 3.19* (1.06, 9.60)
Employment status
(Not full-time) Full-time 2.25 (0.64, 7.95)
Residence in childhood (West upper)
East lower 0.73 (0.20, 2.70) 1.42 (0.24, 8.28) 0.57 (0.11, 3.06)
West lower 1.32 (0.29, 5.89) 3.13 (0.54, 18.24) 2.89 (0.45, 18.70)
East upper 1.30 (0.41, 4.15) 1.84 (0.40, 8.54) 0.75 (0.14, 4.15)
Index for TSP exposure (median) >median 1.78 (0.41, 7.66) 1.58 (0.19, 12.96) 0.46 (0.06, 3.40)
Index for PM3.3 exposure (median) >median 0.44 (0.05, 3.62) 0.43 (0.03, 5.68) 0.28 (0.02, 5.15)
Index for SO2 exposure (median) >median 0.31 (0.02, 3.99) 0.98 (0.11, 8.92) 2.73 (0.24, 30.82)
Specificity (%) 59.4 51.8 73.6
Sensitivity (%) 87.9 71.4 70.6
Rho-square 0.12 0.12 0.12
p < 0.05; **p < 0.01; ***p < 0.001.
Copyright © 2013 SciRes. JEP
Childhood Exposure to Air Pollution as a Potential Contributor of Chronic Non-Respiratory Inflammatory Disorders: A
Longitudinal Prospective Cohort Study in Hamilton, Canada
Copyright © 2013 SciRes. JEP
786
increase, there is a need for large scale longitudinal epi-
demiological studies that assess the impacts of early
childhood exposure to diverse levels of air pollutants on
non-respiratory inflammatory diseases in adulthood. Ex-
posure to TSP and PM3.3 in 1980/1, 1981/2, 1983/4, and
1985/6, and exposures to SO2 in 1978/9, 1980/1, and
1981/2 did not predict any of the examined non-respira-
tory health outcomes. Surprisingly, results suggest that
long-term exposure to PM3.3 decreases the odds of ar-
thritis/rheumatism for females. These results may be at-
tributed to the margin of error and deserve further in-
vestigation particularly given that the health impacts of
exposure to PM are well supported by biological and
epidemiological evidence.
Thirdly, other significant predictor variables of arthri-
tis/rheumatism or high blood pressure/hypertension in-
clude residential exposures to gas/dust/contaminants,
experiencing stressful life events, childhood family in-
come, current family income, property ownership, em-
ployment status, adult body mass index, and persistent
cough in childhood. Results suggest that residential ex-
posures may be predictors of arthritis/rheumatism. It is
understandable that diagnosis with arthritis/rheumatism
may be associated with experiencing two or more stress-
ful life events, given that such chronic conditions can
have an impact on psychological and social health. In
relation to physiological factors, persistent day/night
cough in childhood predicts arthritis for males, whereas
for females a body mass index greater or equal to 25 pre-
dicts high blood pressure. In terms of behavioral and
psychological factors, significant predictors include
regular physical activity and feelings about income. Re-
sults suggest that females who perform regular physical
exercise, that are currently below the low-income cut-off,
and that have an air conditioner have increased odds of
diagnosis with arthritis/rheumatism. This is not surpris-
ing given that regular physical exercise and the use of air
conditioner to keep the environment at a constant tem-
perature are advisable treatments for people with arthritis
or rheumatism.
This research was subject to certain limitations. First,
the sole use of self-reported data limits findings due to
the potential of differential recall bias, particularly in
relation to residential and occupational exposures to dust
or contaminants. Participants who are facing chronic
health problems are more likely to recall and report past
exposures than participants who are in good health. Sec-
ond, the absence of data on exposure assessment to air
pollution past childhood limited analysis on the health
impacts of chronic exposure to air pollution across the
life course, and prevented analysis on whether exposure
to improved air quality has a reverse effect on health.
Thirdly, certain limitations are related to the absence of
data from childhood such as participation levels in out-
door activities or time spent outdoors in childhood. Fourthly,
the definition of the four geographical neighborhoods
may have affected results of analysis of the role of loca-
tion of residence in childhood on long-term health, par-
ticularly given that the east and west neighborhoods were
divided arbitrarily. Finally, despite the fact that loss to
follow-up is consistent with usual migration patterns, the
possibility of selection bias still exists and is a limitation
to this study. In addition, this research could have bene-
fited from longitudinal physiologic measures that are
capable of assessing various biological markers of in-
flammation, oxidative stress, and platelet activation.
5. Acknowledgements
We would like to thank Michelle Vine for her help in the
data collection phase of this research.
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