Abstract

Asthma
is a chronic disease that affects the airways in the lungs. It is common in
childhood and globally accounts for an estimated 7 % of disability life-years among
the 5 to 14-year-age group. (Favarato, G., Anderson, H., Atkinson, R., Fuller,
G., Mills, I., & Walton, H., 2014). According to the Center for Disease and
Control, asthma costs the United States $56 billion each year. The average
yearly cost of care for a child with asthma was $1,039 in 2009. (CDC.) Approximately
9 people die from asthma each day, and in 2009, 3,388 people died from asthma.
(CDC.)  In the last decade, the
proportion of people with asthma in the United States grew by nearly 15%. (CDC.)
Because of the severity of this respiratory disease, a lot of research has been
conducted in order to analyze the factors in which increases the risk of an
asthma attack. Some of these factors include allergens (like pollen, mold,
animal dander, and dust mites), exercise, occupational hazards, tobacco smoke,
air pollution, and airway infections. (CDC.)

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Introduction

One
of the most common respiratory diseases, asthma affects the lives of approximately
18.4 million adults in the United States. (CDC.) The Healthy People 2020
objective is to reduce asthma deaths, reduce hospitalizations for asthma,
reduce emergency department visits for asthma, reduce activity limitations
among persons with current asthma and reduce the proportion of people with
asthma who miss days of work or school. They aim to increase the proportion of
persons with current asthma who receive formal patient education, increase the
proportion of persons with current asthma who receive appropriate asthma care
according to National Asthma Education and Prevention Program (NAEPP)
guidelines, and increase the number of states, territories, and the District of
Columbia with a comprehensive asthma surveillance system for tracking asthma
cases, illness, and disability at the state level.

According
to the data from Healthy People 2020, 3.4 asthma deaths per million children
and adults under age 35 years, 11.0 asthma deaths per million adults aged 35 to
64 years, and 43.4 asthma deaths per million adults aged 65 years and over all occurred
in 2007. 41.4 hospitalizations for asthma per 10,000 children under age 5
years, 11.1 hospitalizations for asthma per 10,000 children and adults aged 5
to 64 years, and 25.3 hospitalizations for asthma per 10,000 adults aged 65
years and over also occurred in 2007.

The
target is to slightly reduce and increase these numbers by the year 2020. With
extensive research done on the topic of asthma, a common source of data comes
from areas most affected by air pollution. According to the World Health
Organization, as urban air quality declines, the risk of stroke, heart disease,
lung cancer, and chronic and acute respiratory diseases, including asthma,
increases for the people who live in urban areas.

Summary
of Table of Evidence

Ambient
air pollution and respiratory outcomes including risk of asthma, asthma related
hospitalizations, poor asthma control, overall lung function impairment and
reduced response have been linked. (Neophytou, A. M.,
White, M. J., Oh, S. S., Thakur, N., Galanter, J. M., Nishimura, K. K., . . .
Burchard, E. G., 2016.) Evidence
shows that air pollution exists more in the cities than elsewhere due to
factors such as traffic. According to one study, ambient nitrogen dioxide is a
widely available measure of traffic-related air pollution and is inconsistently
associated with the prevalence of asthma symptoms in children. (Favarato, G., Anderson, H., Atkinson, R., Fuller, G., Mills,
I., & Walton, H., 2014.)

Also according to the same study, a number of
studies have observed associations between the incidence and/or prevalence of
asthma and variations in long-term exposure to nitrogen dioxide within urban
environments in which traffic emissions are the main source of pollution. (Favarato,
G., Anderson, H., Atkinson, R., Fuller, G., Mills, I., & Walton, H., 2014.)
Evidence
for pollution in the cities can also be found based on these four variables
typically found in cities which have been used to study asthma and air pollution:
traffic exhaust, long range transport, soil and road dust, and coal/oil
combustion. (Halonen, J., Lanki,T., Yli-Tuomi, T., Kulmala, M., Tiittanen, P.,
Pekkanen, J., 2007.)

Through systematic review and meta-analysis,
one study strengthened the evidence for an association between NO2 and asthma
among within-community studies in which the exposure contrast is due to traffic
proximity. Their findings showed that NO2 or correlated pollutants may make a
small proportional contribution to asthma prevalence in children. (Favarato,
G., Anderson, H., Atkinson, R., Fuller, G., Mills, I., & Walton, H., 2014.)

Studies have also analyzed asthma in terms of
asthma control, a major goal in asthma management. Of the 481 subjects included
in the analysis, 44% had controlled asthma, 29% had partly asthma, and 26% had
uncontrolled asthma. Those with lower education levels and high smoking levels
had the least controlled asthma. The results also suggested that long-term
exposure to PM10 and 03 is associated with uncontrolled asthma in adults,
defined by symptoms, exacerbation and lung function. Asthma was more often
uncontrolled in women with a p value of 0.04, and in older subjects with a p
value of 0.003. (Bénédicte Jacquemin, Francine Kauffmann, Isabelle Pin, Nicole
Le Moual, Jean Bousquet, Frédéric Gormand, . . . Valérie Siroux, 2012.)

Factors such as age have also been analyzed
in a study whose purpose was to determine the effects of daily variation in levels
of different particle size fractions and gaseous pollutants on asthma and COPD
by age group. By obtaining data on hospital emergency room visits for 1998–2004
for all three public hospitals in the Helsinki metropolitan area, the study was
able to find that the mechanisms of the respiratory effects of air pollution,
and responsible pollutants, differ by age group. (Halonen, J., Lanki,T.,
Yli-Tuomi, T., Kulmala, M., Tiittanen, P., Pekkanen, J., 2007.)

In
analyzing socioeconomic status as it relates to asthma, one study observed stronger
air pollution–pediatric asthma associations in ‘deprivation areas’ (eg, ?20% of
the ZCTA population living in poverty) compared with ‘non-deprivation areas.’ (O’Lenick, C. R., Winquist, A., Mulholland, J. A.,
Friberg, M. D., Chang, H. H., Kramer, M. R., . . . Sarnat, S. E., 2017.) The
study showed that children living in low socioeconomic environments appear to
be especially vulnerable given positive ORs and high underlying asthma ED
rates.

According
to this study, pathways through which low socioeconomic status may lead to
increased susceptibility to air pollution-related childhood asthma include
higher exposures to outdoor and indoor air pollutants, greater psychosocial
stress associated with the social environment. This includes neighborhood
poverty, neighborhood crime levels, parental unemployment, and reduced access
to local resources such as healthy food options, green space, and healthcare
access. (O’Lenick, C. R., Winquist, A., Mulholland, J. A., Friberg, M. D.,
Chang, H. H., Kramer, M. R., . . . Sarnat, S. E., 2017.)

Another
analysis of the occurrence of asthma in the inner cities dealt with those more
likely to live in the city. One study that set out to assess the relationship
between air pollution and lung functionality in minority children with asthma
and possible modification by global genetic ancestry found that particulate
exposures are associated with reduced lung function in these minority
populations. Global genetic ancestry did not appear to significantly modify
these associations, but percent African ancestry was a significant predictor of
lung function. (Neophytou, A. M., White, M. J., Oh, S. S., Thakur, N.,
Galanter, J. M., Nishimura, K. K., . . . Burchard, E. G., 2016.)

According
to the study, this study is the first to report an association between exposure
to particulates and reduced lung function in minority children in which racial/ethnic
status was measured by ancestry-informative markers.

The data presented shows that the main disparities
that exist in terms of vulnerability to asthma and/or an asthma attack include
location as well as wealth, education, and age. Some
of the studies sought to create laws targeting air pollution, such as traffic
laws, whereas other studies analyzed the biological aspects of asthma, such as
ancestry. A common similarity in the research was that the location of all of
the subjects were selected from a major city.

 

Gaps
in Research

In some of the research, a few limitations
in analysis were present. Factors such as knowledge of asthma control being
self-reported did not account for any falsification of information. (Bénédicte
Jacquemin, Francine Kauffmann, Isabelle Pin, Nicole Le Moual, Jean Bousquet,
Frédéric Gormand, . . . Valérie Siroux., 2012.) Also in this study, there was
no reason mentioned when discussing why asthma was often more uncontrolled in
women and older subjects. In another study that addressed age, the findings
indicated that the mechanisms of the respiratory effects of air pollution, and
responsible pollutants, differ by age group, but also did not explain the
effects of age on asthma. (Halonen, J., Lanki,T., Yli-Tuomi, T., Kulmala, M.,
Tiittanen, P., Pekkanen, J., 2007.)

In another study, traffic pollution
estimates that were based on distance from the road or categorical divisions of
pollutant concentration were excluded from the review, leaving out the
potential effects of these variables. (Favarato, G., Anderson, H., Atkinson,
R., Fuller, G., Mills, I., & Walton, H., 2014.) Also in this study,
researchers noted that there was a tendency for the larger effects to be based
on study monitors, most of which were situated at the child’s school and for
the smaller effects to be based on dispersion models, but that they did not
have sufficient statistical power to confirm this relationship. They also added
that none of the studies compared different methods of exposure assessment
within the same study. (Favarato, G., Anderson, H., Atkinson, R., Fuller, G.,
Mills, I., & Walton, H., 2014).

In one study, researchers noted several
limitations to their study, including small differences in ORs across strata.
The example provided was ORs for EC stratified by increasing quartile of per
cent below poverty: 1.029, 1.004, 1.001, 1.016. They explained that the small
ORs indicate that the contribution of air pollution to asthma emergency
department visits may be small relative to other risk factors. They discussed their
assumption that ZCTA boundaries were relevant socioeconomic environments with
regard to air pollution vulnerability admitting, however, that other scales may
also be relevant, and the relevance of specific scales may vary by geographical
location due to regional patterns of urban development. They also mentioned
that they used 12×12 km pollution grids, a relatively large area, to assess
exposure to air pollutants to estimate daily ZCTA-level air pollution
concentrations. (O’Lenick, C. R., Winquist, A., Mulholland, J. A., Friberg, M.
D., Chang, H. H., Kramer, M. R., . . . Sarnat, S. E., 2017.) These limitations
could pose as possible causes for errors in the research.

In another study that set out to test
genetics and asthma, 1,449 Latino children from five regions, (Chicago, IL,
Bronx, NY, Houston, TX, San Francisco Bay Area, CA and Puerto Rico) and 519
African American children from the San Francisco Bay Area made up the study
population. The study population consists mostly of subjects from urban areas
and does not account for populations from rural areas, skewing the findings to
be more of a result of location than the result of genetics which the study
attempted to test. Similar to another study, demographic information, medical
histories, environmental exposures, and residential histories were obtained
through questionnaires administered by trained bilingual interviewers, which
does not account for falsification of information. (Neophytou, A. M., White, M.
J., Oh, S. S., Thakur, N., Galanter, J. M., Nishimura, K. K., . . . Burchard,
E. G., 2016).

A few other gaps in the research include
the effects of other diseases on asthma, the success or failure of recent
asthma treatments, a comparison between asthma in rural areas as well as urban
to test the hypothesis that asthma sufferers in the cities suffer worse than
those in rural areas, and direct links between the amount of pollution and the
severity of asthma.

 

Conclusion

Due to the severity of risks associated
with asthma (such as death and hospitalization), extensive research has been
done to analyze the factors contributing to asthma. An objective of Healthy
People 2020 is to reduce the outcomes of asthma and increase education and
access to care. Several studies show that vulnerability to asthma and/or an
asthma attack include location (proximity to air pollution, areas of poverty,
and traffic), wealth (socioeconomic status), education (high school versus
undergraduate and beyond), and age (older people having increased uncontrolled
asthma). Though there are a few gaps in the research, there is enough evidence
that links the prevalence of risk factors of asthma to the inner cities.

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