# Quantifying urbanome profiles as potential determinants of asthma and allergies

Marwan El Homsi, Luciana Kase Tanno, Isabella Annesi-Maesano

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Marwan El Homsi, Luciana Kase Tanno, Isabella Annesi-Maesano. Quantifying urbanome profiles as potential determinants of asthma and allergies. Journal of Allergy and Hypersensitivity Diseases, 2024, 3-4, pp.100015. 10.1016/j.jahd.2024.100015. hal-05294388

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Original article

# Quantifying urbanome profiles as potential determinants of asthma and allergies

<figure><img src="image_2.png" /></figure>

Marwan El Homsi<sup>a,*</sup>, Luciana Kase Tanno<sup>a, b</sup>, Isabella Annesi-Maesano<sup>a, b</sup>

## ARTICLE INFO

**Keywords:**

Air pollution

Epidemiology

Exposome

Urban environment

Urbanome

## ABSTRACT

**Introduction:** Urban environmental factors - the so-called urbanome - have a major influence on the health of city dwellers, including allergic and respiratory health that strongly depend on urban lifestyle and setting. Using data from a cross-sectional study, we describe the urbanome of Montpellier, France, as perceived by city dwellers, and identify associated profiles of exposure in view of prevention against allergic and respiratory diseases.

**Methods:** A cross-sectional study was conducted in the Montpellier metropolitan area between November 2022 and September 2023, involving 397 participants aged 18 to 80 years drawn from the general population. Urbanome data were collected using a standardized self-report questionnaire. Fifteen factors were used to identify exposure profiles using a hierarchical clustering on principal components (HCPC) analysis based on a multiple correspondence analysis (MCA) taking gender and smoking into account.

**Results:** Traffic air pollution (94.39 %), noise disturbance (74.94 %), vegetation around home in private area (67.42 %), sport activity (60.20 %), and passive smoking (50.82 %) were the most reported urbanome factors. Two separate clusters were identified, one containing well-known risk factors for allergic or respiratory diseases such as air and noise pollution and the other factors protective for allergic or respiratory diseases such as green spaces. Allergy diagnosis was commoner in the risk factors cluster (34.48 % versus 52.38 %, *p* = 0.011).

**Conclusions:** Data collected in Montpellier showed two patterns of urbanome perception, including risk and protective factors respectively. Such information is useful for promoting prevention measures. Studies with larger numbers of participants, a greater number of more objectively measured environmental factors are needed to further investigate the associations between urbanome and health.

## 1. Introduction

The world population is continuously growing, and the proportion of individuals living in urban areas follows the same trend. Projections suggest a 13.2 % increase in the urban population by 2050 compared to 2018, leading to almost 70 % of the world population living in cities [1]. This demographic shift has made urban health a major public health concern. In urban environments, the general health status and deterioration in quality of life can stem from the over-representation of health risk factors [2]. Asthma and allergies represent a significant burden on global health, impacting individuals, healthcare systems, and economies [3,4]. According to the World Health Organization (WHO), one individual out of two will suffer from asthma or allergies by 2050, which means over 3 billion people living in urban settings [5].

Current studies on the impact of the urban environment on health have focused mainly on a single environmental factor at once. Air pollution is a notable example of a major risk factor among urban environmental factors that affect health. As a result of individual transport, industrial activities, and other combustion uses, including urban heating and other human activities, air pollution has an impact on allergic and respiratory diseases [6–8]. Air pollution is one of the factors on which it is possible to act directly in order to influence the exposure levels of citizens to this source, by reducing emissions among others, and thus the occurrence of allergic and respiratory events [9–11]. Overall, the characterization of exposures that may be protective or at risk for health events within the same environment remains poor. Moreover, individual exposure is the result of a wide range of exposure factors, and even of interactions or cocktail effects that can affect the health of citizens, have

**Abbreviations:** HCPC, hierarchical clustering on principal components; MCA, multiple correspondence analysis; IRB, institutional review board; WHO, World Health Organization.

* Corresponding author.

E-mail address: marwan.el-homsi@inserm.fr (M. El Homsi).

<footnote><sup>a</sup> Desbrest Institute of Epidemiology and Public Health, université de Montpellier, Inserm, Montpellier, France</footnote>

<footnote><sup>b</sup> Division of Pneumology, Allergology and Thoracic Oncology, centre hospitalier universitaire de Montpellier, Montpellier, France</footnote>
been neglected [12,13]. Yet, considering the urban environment as a
whole is of interest to better understand the aggravation and onset of a
pathology including asthma and allergies. Living in an urban environ-
ment has been linked to a higher prevalence of asthma and allergies
compared to rural areas [14,15]. By understanding the link between
urban living and increased risk of asthma and allergies, we can develop
strategies to create healthier urban environments and prevent against
their development.

In analogy with the exposome concept, that consists in the totality of
environmental exposure to which an individual is exposed during his/her
life that can explain multifactorial diseases' development [16], the
urbanome concept has been introduced to gather all the environmental
urban factors that an individual encounters while living in a town. This
allows to acknowledge the fact that most multifactorial diseases arise in
city residents from a complex interplay of various exposures throughout
life. The urbanome approach is very recent and has been only rarely used
in environmental epidemiology (M. El Homsi, L.K. Tanno, I. Annesi-
Maesano, Urbanome and respiratory health. A narrative review.
Submitted for publication). Its aims is to screen and assess the maximum
number of exposures and their interactions in the urban environment in
view to better understand health outcomes.

In Western countries, the urban environment contains a wide variety
of factors, including outdoor and indoor air pollution; noise pollution; the
presence of green, blue, and gray spaces; and factors associated with the
layout of this urban environment, such as the cleanliness of streets and the
presence of public transport [17]. Such urbanome factors can vary
depending on the structure of the city, culture, and way of life in the
country.

In this context, local collection of comprehensive epidemiological
environmental data is essential to assess the impact of the urban
environment on the health of citizens. To contribute to the study of the
urbanome, in our study we consider real-life data from the city of
Montpellier.

Using population-based drawn data from a cross-sectional study, we described the urbanome of Montpellier in France, as perceived by the study participants. Knowing the perception of risk factors is useful to empower individuals and communities to take preventative measures, potentially leading to better health outcomes.

## 2. Materials and methods

This study was conducted as part of the European Urbanome Project using data from a cross-sectional study conducted in Montpellier. Montpellier is a city in the south of France with 302,454 inhabitants in 2021 according to the Insee: https://www.insee.fr/. This city has all of the common features of a traditional urban area, such as public transportation, nearby airport, and high-speed roads. However, its proximity to the sea, mountains, and forests is also a special feature. This study received ethical approval by the institutional review board (IRB) of the centre hospitalier universitaire de Montpellier, number IRB-MTP_2022_06_202201156.

### 2.1. Study population

Calls via social networks, public conferences, and communications
via the Montpellier metropolitan authority were used to recruit
participants at the general population level. The study selection criteria
were as follows: age between 18 and 80 years, living in the Montpellier
metropolitan area for at least one year, and giving their consent to
participate in the study (free and informed consent). The survey
recruitment ran for 11 months, between November 2022 and
September 2023, and allowed the collection of health and urban
exposure data from a sample of people living in Montpellier.
Participants were invited to fill a standardized questionnaire composed
of questionnaires on sociodemographic characteristics, urbanome
factors and health, which allowed us to count the number of individuals

with a diagnosis of allergy. The questionnaire was completed online by
the participating individuals.

### 2.2. Urbanome data

Data on exposures to urban environmental factors were measured in a broad sense using a questionnaire derived from the LARES developed by the WHO [18]. Out of 42 initial environmental exposures that were present in the questionnaire, due to a response rate below 20% or to high correlations between the variables, 15 were considered in this study. This reduction was performed to ensure independence among the factors considered. They belonged to four major families: air pollution, noise pollution, urban quality, and lifestyle. Individuals with no response to the exposure question (n = 29 at maximum) were indicated as unexposed to the risk factor. The list of measured exposures and their coding is available in the Appendix (Table S1).

### 2.3. Statistical methods

The statistical analysis described the perception of the urbanome in
Montpellier and established exposure perception profiles.

#### 2.3.1. Descriptive epidemiology analysis

The distributions of urban exposures perception by Montpellier
inhabitants were given as means, medians, and standard deviations for
each quantitative variable as well as the number of observations and
percentages for the qualitative variables.

#### 2.3.2. Cluster analysis

Cluster analysis was used to group similar exposures data points
together as a powerful tool for uncovering hidden patterns and structures
within the dataset. More in detail, hierarchical clustering on principal
component (HCPC) analysis was performed based on a multiple
correspondence analysis (MCA) using the fifteen urbanome factors
retained in our study data, as well as sex and smoking status [19,20]. Age
was not included due to small age differences in the population. Due to the
homogeneity of age in the sample, this variable was not taken into
account. Classical Fisher's exact and chi-square tests were used to
compare the proportion of variables in the clusters. HCPC and MCA were
performed using FactoMineR [21] and factoextra packages on R [22].

For all statistical tests, α was set at 0.05 and all tests were two-tailed.
Statistical analyses were performed using R version 4.3.3.

## 3. Results

Out of the initial 673 individuals accepting to participate in the
Urbanome Montpellier study, the 397 living in Montpellier were included
in the present analysis. Indeed, since the Urbanome Montpellier study was
conducted in the entire Montpellier metropolitan area, which includes
both rural and semi-urban areas, only the participants living in the city of
Montpellier, of utility in the study of the urbanome, were retained as
informative in the investigation of the urbanome. Differences in terms of
age, sex, socioprofessional status, tobacco consumption, and marital
status between the population before and after eliminating people who
had not participated or had been included in the entire study were not
significant. The participants were 67.51 % female, with a mean age of 46
years (Table 1), belonging to high socioeconomic classes (42.68 %), and
had an average body mass index of 23.63 kg/m². Of the participants,
20.91 % reported smoking and 63.04 % were in couple, married or not.
Among them 42.00 % had a diagnosis of allergy.

Of the 15 urban factors studied, the most frequently reported by the
study population were traffic-related air pollution (94.39 %), noise from
urban activities (91.50 %), overall noise pollution (74.94 %), the presence
of vegetation around the home in private areas (67.42 %), the use of
public transport (62.88 %), and the practice of sporting activities (60.20
%) (Table 2).
<table><caption>**Table 1**

Description of an urbanome: distribution of study population characteristics in Montpellier (France), *n* = 397.</caption><thead><tr><th>Characteristics</th><th>n</th></tr></thead><tbody><tr><td>Sex, n (%)</td><td>397</td></tr><tr><td>Female</td><td>268 (67.51)</td></tr><tr><td>Male</td><td>129 (32.49)</td></tr><tr><td>Age, mean (median, SD)</td><td>397</td></tr><tr><td>Body mass index, mean (median, SD)</td><td>392</td></tr><tr><td>Marital status, n (%)</td><td>395</td></tr><tr><td>Single/divorced/widowed</td><td>146 (36.96)</td></tr><tr><td>In a relationship (unmarried)</td><td>143 (36.20)</td></tr><tr><td>Married</td><td>106 (26.84)</td></tr><tr><td>Socioprofessional status, n (%)</td><td>396</td></tr><tr><td>Unemployed/student</td><td>51 (12.88)</td></tr><tr><td>Retired</td><td>59 (14.90)</td></tr><tr><td>Employee, intermediate profession, worker</td><td>99 (25.00)</td></tr><tr><td>Craftsman, merchant, business owner</td><td>18 (4.55)</td></tr><tr><td>Manager and higher intellectual profession</td><td>169 (42.68)</td></tr><tr><td>Smoking, n (%)</td><td>397</td></tr><tr><td>Yes</td><td>83 (20.91)</td></tr><tr><td>Allergy diagnosed, n (%)</td><td>200</td></tr><tr><td>Yes</td><td>84 (42.00)</td></tr></tbody></table>

Cluster analysis showed that in terms of the perception of the urbanome, participants were shared between two distinct groups (Fig. 1).

On the one hand, people in Cluster 1 reported to be more exposed to good street cleanliness, green spaces, and vegetation around their homes in a public or private area or in front of their window or balcony than the others (Table 3). On the other hand, people in Cluster 2 reported that they were more exposed to traffic air pollution, poor outdoor and indoor air quality, noise disturbance, and vegetation around their homes than the others. Individuals in Cluster 2 (risk factors cluster) had more diagnosed allergies than those in Cluster 1 (protective factors cluster) (34.48 % versus 52.38 %, *p* = 0.011) (data not shown). No significant differences between clusters 1 and 2 in exposure to molds, presence of vegetation along the street, passive smoking, and the use of public transportation, or in sex, sport activities, were observed. No significant differences were found within the two established clusters in terms of gender, age, marital

<table><caption>**Table 2**

Distribution of the studied urbanome factors in Montpellier (France), *n* = 397.</caption><thead><tr><th colspan="2">Exposure</th></tr></thead><tbody><tr><td colspan="2">Outdoor air pollution</td></tr><tr><td>Traffic air pollution, %</td><td>94.39</td></tr><tr><td>Poor outdoor air quality, %</td><td>32.30</td></tr><tr><td colspan="2">Indoor air pollution</td></tr><tr><td>Mold, %</td><td>29.46</td></tr><tr><td>Poor indoor air quality, %</td><td>43.95</td></tr><tr><td colspan="2">Lifestyle</td></tr><tr><td>Sport, %</td><td>60.20</td></tr><tr><td>Passive smoking (no smoking), %</td><td>50.82</td></tr><tr><td>Noise pollution</td><td></td></tr><tr><td>Noise Disturbance, %</td><td>74.94</td></tr><tr><td colspan="2">Urban quality</td></tr><tr><td>Good street cleanliness, %</td><td>37.24</td></tr><tr><td>Green space, %</td><td>58.97</td></tr><tr><td>Vegetation around home, %</td><td>5.81</td></tr><tr><td>Vegetation along street, %</td><td>48.48</td></tr><tr><td>Vegetation public area, %</td><td>33.84</td></tr><tr><td>Vegetation private area, %</td><td>67.42</td></tr><tr><td>Vegetation window balcony, %</td><td>39.14</td></tr><tr><td>Use of public transportation, %</td><td>62.88</td></tr></tbody></table>

status, residential area (ZIP code), and body mass index (data not shown). Although not significant, a trend was observed for socio-economic status with more managers and higher intellectual professions in cluster 1 (*p* = 0.2) (data not shown).

## 4. Discussion

The cross-sectional study conducted in Montpellier allowed identifying the urbanome in a population-based sample of 397 city inhabitants drawn from the general population. Results showed that the most reported exposure factors were traffic air pollution and noise. Only 5 % of individuals were not bothered by air pollution and 8 % from noise. The study population also reported being exposed to vegetation and green spaces, and practiced physical activity. Interestingly, our data also

<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Visualization of cluster structure in Montpellier study population (*n* = 397) through hierarchical cluster analysis on multiple correspondence analysis.</figcaption></figure>
<caption>**Table 3**</caption>

Proportions of the urbanome factors in Montpellier (France) within the cluster analysis, n = 397.

<table><thead><tr><th>Variable</th><th>Cluster 1, n = 215</th><th>Cluster 2, n = 182</th><th>p</th></tr></thead><tbody><tr><td>Outdoor air pollution</td><td></td><td></td><td></td></tr><tr><td>Traffic air pollution, %</td><td>87.91</td><td>99.45</td><td>&lt;0.001<sup>2</sup></td></tr><tr><td>Poor outdoor air quality, %</td><td>5.58</td><td>62.09</td><td>&lt;0.001<sup>1</sup></td></tr><tr><td>Indoor air pollution</td><td></td><td></td><td></td></tr><tr><td>Mold, %</td><td>26.51</td><td>28.57</td><td>0.7<sup>1</sup></td></tr><tr><td>Poor indoor air quality, %</td><td>16.28</td><td>72.53</td><td>&lt;0.001<sup>1</sup></td></tr><tr><td>Lifestyle</td><td></td><td></td><td></td></tr><tr><td>Sport, %</td><td>61.86</td><td>58.24</td><td>0.5<sup>1</sup></td></tr><tr><td>Passive smoking (no smoking), %</td><td>43.72</td><td>51.10</td><td>0.2<sup>1</sup></td></tr><tr><td>Noise pollution</td><td></td><td></td><td></td></tr><tr><td>Noise disturbance, %</td><td>56.28</td><td>94.51</td><td>&lt;0.001<sup>1</sup></td></tr><tr><td>Urban quality</td><td></td><td></td><td></td></tr><tr><td>Good street cleanliness, %</td><td>55.35</td><td>14.84</td><td>&lt;0.001<sup>1</sup></td></tr><tr><td>Green space, %</td><td>72.56</td><td>40.66</td><td>&lt;0.001<sup>1</sup></td></tr><tr><td>Vegetation around home, %</td><td>0.47</td><td>12.09</td><td>&lt;0.001<sup>2</sup></td></tr><tr><td>Vegetation along street, %</td><td>49.30</td><td>47.25</td><td>0.7<sup>1</sup></td></tr><tr><td>Vegetation public area, %</td><td>48.84</td><td>15.93</td><td>&lt;0.001<sup>1</sup></td></tr><tr><td>Vegetation private area, %</td><td>80.93</td><td>51.10</td><td>&lt;0.001<sup>1</sup></td></tr><tr><td>Vegetation window balcony, %</td><td>54.88</td><td>20.33</td><td>&lt;0.001<sup>1</sup></td></tr><tr><td>Use of public transportation, %</td><td>63.72</td><td>61.54</td><td>0.7<sup>1</sup></td></tr><tr><td>Other</td><td></td><td></td><td></td></tr><tr><td>Sex, %</td><td></td><td></td><td>&gt;0.9<sup>1</sup></td></tr><tr><td>Female</td><td>67.44</td><td>67.58</td><td></td></tr><tr><td>Male</td><td>32.56</td><td>32.42</td><td></td></tr><tr><td>Smoking, %</td><td>21.40</td><td>20.33</td><td>0.8<sup>1</sup></td></tr></tbody></table>

describe two distinguished patterns as assessed by cluster analysis of the urbanome perception, separating protective and risk factors. The separation was a clear and interpretable. However, no significant differences were found within the two established clusters in terms of the available variables but in the case of the occupation with more managers and higher intellectual professions in cluster 1, although not significantly. Unfortunately, our dataset did not allow to better explore these differences in individuals' behavior. The former cluster contained individuals that reported to be more exposed than those of the other cluster to factors such as green spaces, vegetation, and street cleanliness, which are protective for health, although these relationship remain controversial, mainly regarding asthma and allergies [23–28]. Although, the relationship between allergic and respiratory health and city or street cleanliness has not been investigated, the adverse effects of exposure to waste and its by-products are well-known in the case of asthma [33–35]. The risk factors of the second cluster included outdoor and indoor air pollution and noise that have been associated with allergic and respiratory diseases [29–34]. Interestingly, individuals in this cluster had more diagnosis of allergy than others (34.48 % versus 52.38 %, p = 0.011). The existence of distinct patterns is important to be known to obtain effective prevention and target appropriate individuals.

Our study has several limitations. The study population was homogeneous and unrepresentative of the Montpellier general population. Hoverer, our participants were drawn from the general population using a spread channel of recruitment. Most respondents were women, and the average age of the participants was higher than that of the Montpellier population. In addition, the participants in our study belonged more to high socio-professional category, which is not representative of the general population in Montpellier. Recruitment methods, particularly the use of social networks such as Facebook, mainly influenced the population recruitment by amplifying the participation of people with high social criteria and middle age. In particular, those who accepted to participate were generally concerned about the study or about a pathology associated with the urban environment. Overall,

despite the resources employed, recruitment in the context of a participatory study was complicated, which explains the low number of participants and the multiplicity of recruitment methods that biased the final population. As recruitment for this study lasted a full year and surveys were carried out at different time periods, it is possible to hypothesize that responses may have been influenced by temporal variables, notably season, which can influence the perception of the urban environment [35]. However, seasonality of some environmental factors that may have an impact on asthma [36] and allergy [37] could not be taken into account at the individual level. Lastly, exposure to the urbanome was measured using an online self-questionnaire, a subjective mode of collection that may bias the measurement of exposure of participants in a non-differential way. However, this questionnaire was standardized. In addition, perception of the risk is crucial for disease prevention, as a good perception of risk factors empowers individuals and communities to take preventive measures, potentially leading to better health outcomes. However, this study is original in its methodology, and provides one of the first analysis of the urban exposome in Montpellier. The results of this study show the distribution of factors associated with the Montpellier urbanome, particularly air pollution, noise pollution, and the general quality of the urban environment are important for the citizens. These are important environmental factors for asthma and allergy [38] due to climate change. The results of this study should contribute to enable larger-scale studies to be conducted to determine the impact of the urbanome on health in order to improve citizens' allergic and respiratory health. More specifically, these results could enable the implementation of recommendations targeted at populations with a majority of allergy and respiratory health risk factors. Such recommendations could help to reduce the impact of these factors of the urbanome on the most exposed and the least risk-aware populations.

## 5. Conclusion

Our data present the urbanome description in Montpellier, identifying air pollution, noise pollution, lifestyle, and the quality of the urban environment in general as factors significantly associated with health in the literature, particularly asthma and allergies. Two separated clusters were identified, one including mostly protective factors and the other including risk factors for these conditions. These original results need to be validated by a study that includes more participants and an investigation of additional factors of exposure to the urban environment, using objectively measured factors.

## Funding

This study was funded by the EU HORIZON 2020 URBAN Observatory for Multiparticipatory Enhancement of health and wellbeing (Urbanome) Project (https://www.urbanome.eu/), grant #945391.

## Declaration of competing interest

No conflict of interest.

## Appendix A. Supplementary data

Supplementary material (Table S1) related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.jahd.2024.100015.

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