Residential greenness, respiratory symptoms and lung function in children, adolescents and adults with asthma: a cross-sectional study.

Abstract

We hypothesize that green areas within cities affect the respiratory symptoms of individuals with asthma, but this effect may not be the same for all age groups, because the immunopathology of asthma in children-adolescents is different from the immunopathology of asthma in adults. The objective of this study is to evaluate whether there is an association between the percentage of green area close to the residence and asthma outcomes, stratified by age group. We included individuals with asthma over the age of ten years. Two independent trained researchers measured, in satellite images, the extent of green area around the residence. The primary outcome of the study was the severity of respiratory symptoms measured by the Asthma Control Test. The secondary outcome was the presence of airway obstruction in the spirometry test carried out on the day of the study visit. Binary logistic regression analyzes evaluated whether the percentage of green area close to the residence was associated with asthma outcomes. In children-adolescents, greater density of green area was associated with a greater frequency of uncontrolled asthma symptoms. In adults, greater density of green area was associated with a lower frequency of uncontrolled asthma symptoms and a lower frequency of airway obstruction. We conclude that the extent of green areas close to the residence is associated with asthma morbidity. The expansion of green areas within cities should favor species that do not disseminate pollen with allergenic potential, especially in regions close to schools and daycare centers.

Full text

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Residential greenness, respiratory symptoms and
lung function in children, adolescents and adults
with asthma: a cross-sectional study.
Raissa Guinossi
Faculdade de Medicina de Jundiaí: Faculdade de Medicina de Jundiai
Cintia Bertagni Mingotti
Faculdade de Medicina de Jundiaí: Faculdade de Medicina de Jundiai
Monique Olivia Burch
Faculdade de Medicina de Jundiaí: Faculdade de Medicina de Jundiai
Luciana Soares
Faculdade de Medicina de Jundiaí: Faculdade de Medicina de Jundiai
Natalia Castanha
Faculdade de Medicina de Jundiaí: Faculdade de Medicina de Jundiai
Ronei Luciano Mamoni
Faculdade de Medicina de Jundiaí: Faculdade de Medicina de Jundiai
Evaldo Marchi
Faculdade de Medicina de Jundiaí: Faculdade de Medicina de Jundiai
Eduardo Ponte
Faculdade de Medicina de Jundiai
Research Article
Keywords: airway, air pollution, environment, urbanization, asthma epidemiology, inhaled corticosteroids,
urban population, hygiene hypothesis, public health, bronchodilators
Posted Date: May 31st, 2024
DOI: https://doi.org/10.21203/rs.3.rs-4426656/v1
License:   This work is licensed under a Creative Commons Attribution 4.0 International License. 
Read Full License

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Abstract
We hypothesize that green areas within cities affect the respiratory symptoms of individuals with
asthma, but this effect may not be the same for all age groups, because the immunopathology of
asthma in children-adolescents is different from the immunopathology of asthma in adults. The
objective of this study is to evaluate whether there is an association between the percentage of green
area close to the residence and asthma outcomes, stratied by age group. We included individuals with
asthma over the age of ten years. Two independent trained researchers measured, in satellite images,
the extent of green area around the residence. The primary outcome of the study was the severity of
respiratory symptoms measured by the Asthma Control Test. The secondary outcome was the presence
of airway obstruction in the spirometry test carried out on the day of the study visit. Binary logistic
regression analyzes evaluated whether the percentage of green area close to the residence was
associated with asthma outcomes. In children-adolescents, greater density of green area was
associated with a greater frequency of uncontrolled asthma symptoms. In adults, greater density of
green area was associated with a lower frequency of uncontrolled asthma symptoms and a lower
frequency of airway obstruction. We conclude that the extent of green areas close to the residence is
associated with asthma morbidity. The expansion of green areas within cities should favor species that
do not disseminate pollen with allergenic potential, especially in regions close to schools and daycare
centers.
Introduction
Urbanization has occurred at an accelerated pace in developing countries.1 Individuals residing in poor
rural areas have migrated to urban regions in search of a better quality of life, while rural areas have been
urbanized as they receive infrastructure.2 This transformation benets the population, which now has
access to health services and basic sanitation and less exposure to indoor smoke from wood stoves.3;4
Nevertheless, urbanization reduces exposure to antigens that are important for the regulation of the
immune response and it is associated with greater exposure to particulate matter and gases that pollute
the air in cities.5;6;7;8
Studies suggest that children and adolescents living in urban areas have a higher risk of atopy and
asthma compared to individuals living in rural areas.9;10;11;12;13 In childhood and adolescence, asthma is
usually atopic; therefore, it is hypothesized that urban environmental exposures induces atopy and,
consequently, the emergence of asthma. This hypothesis is strengthened by studies that have shown
that the intensity of the association between atopy and wheezing in childhood is stronger in urbanized
regions than in rural areas; in other words, atopy seems to be more powerful in inducing asthma among
children and adolescents living in cities.14;15
Urbanization is an irreversible process; therefore, the prevention of asthma morbidity in cities depends
on intervening in the elements of the urban environment that affect asthma outcomes. Green areas
within cities contribute to dispersing air pollutants 16, therefore, they could positively affect the

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respiratory health of individuals with asthma; but green areas also increase the population's exposure to
pollen, which could induce atopy or worsen atopic asthma. 17; 18; 19
Currently, the effect of green areas on the respiratory health of individuals with asthma is unknown. We
hypothesize that green areas within cities affect the respiratory symptoms of individuals with asthma,
but this effect may not be the same for all age groups, because the immunopathology of asthma in
children and adolescents is different from the immunopathology of asthma in adults (20). Therefore, the
main objective of this study is to evaluate whether there is an association between the percentage of
green area close to the residence and the severity of respiratory symptoms in individuals with asthma,
stratied by age group. The secondary objective is to assess whether there is an association between
green areas and the lung function of these individuals.
Material and methods
We conducted this cross-sectional study in Jundiaí, a 400,000-inhabitant city in southeast Brazil. We
screened all consecutive individuals attending a scheduled spirometry test requested by physicians from
any of the 42 public health facilities in the municipality from September 2021 to November 2022.
We included individuals with asthma over the age of ten years; who were living in the city of Jundiai; and
who had lived at the same address during the 24 months prior to the study visit. We excluded current
smokers; smoking history above 10 pack-years; pregnant women; history of tuberculosis treatment;
thoracic surgery; occupational risk factors for COPD or pneumoconiosis; COPD or Asthma-COPD Overlap
Syndrome (ACOS); and individuals unable to achieve American Thoracic Society requirements in the
spirometry test. The institutional review board of the Jundiaí School of Medicine approved the study
(2.198.023); individuals signed the informed consent.
The physician in charge validated the diagnosis of asthma taking into account the interview and physical
examination performed in the study visit, a review of medical records, and an evaluation of current and
previous lung-function test results. Some clinical evidence of asthma were recurrent wheezing, cough or
dyspnea lasting longer than one year; symptoms improvement after ICS maintenance therapy; and
symptoms relief after bronchodilator. The individual should have had some previous exam
demonstrating the variability of the airway caliber. Conrming exams were variation greater than 20% of
the serial expiratory peak-ow; FEV1 variation after BD greater than 12% and 200 ml in a spirometry; or
positive bronchoprovocation test.
Individuals with medical history and physical examination suggestive of asthma but who reported
exposure to indoor wood smoke and had post-BD airway obstruction in the spirometry performed on the
day of the study visit were excluded due to the risk of having ACOS.
The included individuals attended an appointment with a chest physician who interviewed the
participants, reviewed prescriptions and inspected medicines to record the pharmacological treatments
that they had used during the eight weeks preceding the study visit. We instructed in advance that

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individuals bring to the study visit the prescriptions and medications so that the researcher in charge
could accurately quantify the types and doses of medications that they were using. The individuals
underwent spirometry on the day of the study visit.
The diagnosis of diabetes mellitus, hypertension and/or depression concomitant with asthma was
established if the individual was using specic medication for the reported pathology.
We validated the current address of residence reported by the individual against the address available in
the municipal registry. Two independent trained researchers located the residence on satellite images.
Briey, they measured the extent of green area around the residence and the distance from the nearest
route with intense vehicle trac. A third researcher was called in to analyze the images when there was
a discrepancy greater than 5% in measurements made by the rst two researchers (details in the
supplementary le).
We estimated the green area density by calculating the area around the individual's residence occupied
by vegetation. The researchers responsible for measuring this variable identied the individual's address
in the satellite image; framed a space of 1-km2 around the address; and circumscribed the sector
occupied by green area using an application, excluding the sector occupied by buildings (houses,
edices, avenues, highways, or any other type of construction). The application automatically calculates
the area of the circumscribed land. The researcher used this information to calculate the proportion of
green area occupying the 1-km2 around the residence.
The primary outcome of the study was the severity of respiratory symptoms measured by the Asthma
Control Test (ACT). This questionnaire measures the severity of asthma symptoms in a scale from ve to
25, highest values indicating less symptomatology. The 19-point cutoff discriminates between controlled
and uncontrolled asthma. The secondary outcome was the presence of airway obstruction. The criterion
for identifying airway obstruction was a FEV1/FVC ratio below the lower limit of normal in spirometry
performed on the day of the study visit.
We calculated a sample of 352 individuals by age group considering that an increase of one quintile in
the percentage of green area close to the residence would increase the risk of the primary outcome by
35%. The p value was set at 0.05 and the power at 80%.
Binary logistic regression analyzes evaluated whether the percentage of green area close to the
residence (independent variable) was associated with asthma outcomes (dependent variable) (details in
the supplementary le). The independent variable was stratied by quintile and entered into the model as
an ordinal variable. We adjusted the analyzes for age, sex, maintenance therapy, comorbidities, smoking,
distance from the nearest route with intense vehicle trac, season of the year in which the assessment
was carried out and exposure to indoor wood smoke in childhood because these covariates may modify
the relationship between the dependent and independent variables.21;22 It was crucial to adjust the
regressions for the distance from the nearest route with intense vehicle trac because we assumed that
residences located in regions with a higher density of green area would be further away from avenues;

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which could bias the results considering that studies have already shown that living close to routes with
intense vehicle trac worsens asthma outcomes. 23
We also executed linear regression analyzes to assess whether the percentage of green area close to the
residence correlated with the continuous values of the spirometry parameters. Linear regression was
also adjusted for the previously mentioned parameters. (SPSS 25, IBM, Armonk, New York).
Results
We screened 3,199 individuals referred for spirometry test during the recruitment period. Various
respiratory and non-respiratory morbidities justied the spirometry request. We did not enroll 1,769
individuals without asthma. One hundred and forty two individuals were not included because they met
any exclusion criteria. Thus, we enrolled 1288 individuals with asthma, of which 322 individuals under
the age of 18 and 966 at least 18 years of age.
Table1 presents the demographic and clinical characteristics of the children and adolescents included
in the study. The median age was 13 years, 45% were female, few had comorbidities or previous
exposure to indoor wood smoke and the majority were using steps 1 or 2 of the maintenance therapy
recommended by the Global Initiative for Asthma (GINA). The median ACT score was 22, 22% had pre-BD
airway obstruction and 11% had post-BD airway obstruction.
Table2 shows the characteristics of the 966 adults included in the study. The median age was 52 years,
76% were female, the most common comorbidity was systemic arterial hypertension and 39% reported
previous exposure to indoor wood smoke. The majority of individuals were using steps 3 or 4 of the
maintenance therapy proposed by GINA. The frequency of pre- and post-bronchodilator airway
obstruction was 35% and 25%, respectively.
Table3 describes the results of binary logistic regressions that measured the relationship between the
percentage of green areas close to the residence and asthma outcomes in children and adolescents. It
was observed that greater density of green area was directly associated with a greater frequency of
uncontrolled asthma symptoms, but was not associated with airway obstruction. Table4 presents the
results of the regressions with the adult population. In this table, we observed that greater density of
green area was associated with a lower frequency of uncontrolled asthma symptoms and a lower
frequency of post-BD airway obstruction.
Finally, Tables 5 and 6 present crude and adjusted linear regressions that measured the correlation
between the percentage of green area close to the residence and the main spirometry parameters. In the
adult population, there was a correlation between green area and lung function.
Discussion

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The results of this study demonstrate that the extent of green areas close to the residence is associated
with the severity of respiratory symptoms in individuals with asthma. In children and adolescents, green
areas are positively associated with symptom severity. In adults, the association between green areas
and symptom severity is inverse. Studies need to clarify why the effect of green areas on asthma
symptoms differs between children-adolescents and adults. Our best hypothesis to explain this
disagreement is related to immunopathological differences in asthma between age groups. Children and
adolescents have predominantly atopic asthma, therefore, they would be more susceptible to worsening
when exposed to aeroallergens that green areas disseminate into the air, especially grass pollen. 17; 18 In
adults, the proportion of atopic asthma is signicantly lower 20; consequently, adults would be less
susceptible to worsening asthma when exposed to aeroallergens while beneting from the effect of
green areas on the dispersion of air pollution. 16 The results presented in our study suggest that urban
interventions to increase green areas within cities should avoid plant species with allergenic potential,
especially in areas close to schools and daycare centers. 24; 25
In adults, we observed a statistically signicant association between the percentage of green areas
close to the residence and lung function test values. The direction of this association was consistent
with analyzes between green areas and asthma symptoms in this age group. In children and
adolescents, however, the inverse association between greenness and lung function was not statistically
signicant, probably because the number of individuals in this age group was three times smaller.
There are few publications on the effect of green areas on asthma morbidity in children and adolescents.
In Taiwan, the incidence of asthma in this age group increased with increasing exposure to green areas.
26 In a European multicenter study that compiled data from nine cohorts of children, increased
vegetation cover was associated with a greater risk of wheezing complaints and self-reported diagnosis
of asthma. 24 In Italy and Canada, however, studies have shown that living close to green areas was
associated with a lower risk of childhood asthma. 27; 28 It is possible that the inconsistency in the
literature on this topic is related to environmental differences between regions such as the uneven
distribution of plant species that disseminate pollen with allergenic potential. 24; 25 It is not possible to
rule out, however, that the needs and beliefs of the populations may have biased the direction of the
observed associations. For example, it is possible that families with children affected by persistent
asthma prefer to live close to hospitals and clinics, which are usually in the most densely populated
regions. Conversely, it is also possible that parents of asthmatic children could prefer to live near green
areas if they believe it is better for their children's health. Intervention studies are needed to disentangle
the relationship between greenness and asthma morbidity.
We identied some characteristics of our study that differentiate it from previous publications on this
topic. First, we used the clinical and lung function criteria recommended in international guidelines to
dene the diagnosis of asthma while most previous studies labeled individuals complaining of wheezing
or self-reporting the diagnosis of asthma as asthmatics. We adjusted the analyzes for covariates that
certainly affect the relationship between the extent of green areas and asthma outcomes. Among the

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limitations, the cross-sectional design of our study does not allow establishing a cause and effect
relationship between the observed associations. Finally, we did not recruit individuals covered by private
health insurance, but they represent only 10% of the population.
Conclusions
We conclude that the extent of green areas close to the residence is associated with asthma morbidity.
In children and adolescents, the association was direct. In adults, the association was inverse. This
result indicates that the expansion of green areas within cities should favor species that do not
disseminate pollen with allergenic potential, especially in regions close to schools and daycare centers.
Intervention studies are needed to disentangle the relationship between greenness and asthma
morbidity.
Declarations
Funding sources:FAPESP funded this study, grant 2023/07590-0.
Conict of Interest Statement:The authors have no conicts of interest to declare.
Author contribution: Authors contributed equally with data collection, data analysis and manuscript
preparation.
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Tables
Table 1. Demographic and clinical characteristics of children-adolescents enrolled in the study.

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 Children-adolescents
N = 322
Age in years, median (IQ) 13 (11-15)
Female gender, n (%) 146 (45)
BMI, median (IQ) 21 (18-25)
Diabetes mellitus, n (%) 0 (0)
Systemic arterial hypertension, n (%) 1 (<1)
Depression, n (%) 6 (2)
Smoking in pack years , median (IQ) 0 (0-0)
Current exposure to indoor wood smoke, n (%) 0 (0)
Exposure to indoor wood smoke in childhood, n (%) 3 (1)
Green area density, median (IQ) *30 (13-44)
Distance in km from the nearest avenue, median (IQ) 0.70 (0.27-1.47)
Asthma maintenance therapy - GINA, n (%)
      Step 1 or 2
      Step 3 or 4
      Step 5

209 (65)
111 (34)
2 (1)
ACT score - median (IQ) 22 (19-24)
FVC % predict, pre-BD - median (IQ) 104 (95-115)
FVC % predict, post BD - median (IQ) 107 (96-119)
FEV1 % predict, pre-BD - median (IQ) 95 (84-105)
FEV1 % predict, post BD - median (IQ) 102 (92-112)
Pre-BD airway obstruction, n (%) 71 (22)
Post-BD airway obstruction, n (%) 36 (11)
* % of the area occupied by green space within 1 km2 around the residence
Table 2. Demographic and clinical characteristics of adults enrolled in the study.

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 Adults
N = 966
Age in years, median (IQ) 52 (37-66)
Female gender, n (%) 730 (76)
BMI, median (IQ) 30 (26-34)
Diabetes mellitus, n (%) 162 (17)
Systemic arterial hypertension, n (%) 385 (40)
Depression, n (%) 171 (18)
Smoking in pack years , median (IQ) 0 (0-0)
Current exposure to indoor wood smoke, n (%) 0 (0)
Exposure to indoor wood smoke in childhood, n (%) 377 (39)
Green area density, median (IQ) *24 (9-45)
Distance in km from the nearest avenue, median (IQ) 0.55 (0.24-1.17)
Asthma maintenance therapy - GINA, n (%)
      Step 1 or 2
      Step 3 or 4
      Step 5

417 (43)
475 (49)
74 (8)
ACT score - median (IQ) 20 (15-23)
FVC % predict, pre-BD - median (IQ) 87 (75-98)
FVC % predict, post BD - median (IQ) 91 (80-101)
FEV1 % predict, pre-BD - median (IQ) 78 (63-90)
FEV1 % predict, post BD - median (IQ) 84 (70-96)
Pre-BD airway obstruction, n (%) 335 (35)
Post-BD airway obstruction, n (%) 238 (25)
* % of the area occupied by green space within 1 km2 around the residence
Table 3. Binary logistic regression analyzes to evaluate the relationship between the characteristics of
the environment and asthma outcomes in children-adolescents.

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 Crude
OR (95 IC)
Adjusted
OR (95 IC)*
Uncontrolled symptoms
    Green area density **

1.29 (1.07-1.57)

1.25 (1.02-1.54)
Pre-BD airway obstruction
    Green area density **

1.11 (0.92-1.34)

1.11 (0.91-1.37)
Post-BD airway obstruction
    Green area density **

1.05 (0.82-1.34)

1.02 (0.78-1.33)
* Adjusted for age, sex, maintenance therapy, comorbidities, smoking, distance from the nearest avenue,
season of the year in which the assessment was carried out and exposure to indoor wood smoke in
childhood; ** % of the area occupied by green space in the region corresponding to 1 km2 around the
place of residence.
Table 4. Binary logistic regression analyzes to evaluate the relationship between the characteristics of
the environment and asthma outcomes in adults.
 Crude
OR (95 IC)
Adjusted *
OR (95 IC)
Uncontrolled symptoms
    Green area density **

0.86 (0.77-0.96)

0.90 (0.81-0.99)
Pre-BD airway obstruction
    Green area density **

0.93 (0.84-1.02)

0.96 (0.86-1.07)
Post-BD airway obstruction
    Green area density **

0.88 (0.78-0.99)

0.86 (0.78-0.96)
* Adjusted for age, sex, maintenance therapy, comorbidities, smoking, distance from the nearest avenue,
season of the year in which the assessment was carried out and exposure to indoor wood smoke in
childhood; ** % of the area occupied by green space in the region corresponding to 1 km2 around the
place of residence.
Table 5. Linear regression to evaluate the correlation between the extent of the green area close to the
residence and the lung function parameters analyzed as continuous values in children and adolescents.

Page 13/14
 Beta
Crude
p Beta
Adjusted*
p
FEV1 % of predict pre-BD - 0.75 0.18 - 0.90 0.16
FEV1 % of predict post-BD - 0.01 0.86 - 0.01 0.94
FVC % of predict pre-BD 0.02 0.68 0.03 0.63
FVC % of predict post-BD 0.05 0.46 0.05 0.46
* Adjusted for age, sex, maintenance therapy, comorbidities, smoking, distance from the nearest avenue,
season of the year in which the assessment was carried out and exposure to indoor wood smoke in
childhood
Table 6. Linear regression to evaluate the correlation between the extent of the green area close to the
residence and the lung function parameters analyzed as continuous values in adults.
 Beta
Crude
p Beta
Adjusted*
p
FEV1 % of predict pre-BD 0.08 < 0.01 0.08 0.03
FEV1 % of predict post-BD 0.08 < 0.01 0.08 0.03
FVC % of predict pre-BD 0.07 0.04 0.08 0.03
FVC % of predict post-BD 0.06 0.08 0.07 0.06
* Adjusted for age, sex, maintenance therapy, comorbidities, smoking, distance from the nearest avenue,
season of the year in which the assessment was carried out and exposure to indoor wood smoke in
childhood
Figures

Page 14/14
Figure 1
Correlation between the area around the residence occupied by green space and the distance from
routes with heavy vehicle trac (n = 1,288).
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