Attributable fraction to housing mold in cases of asthma in Brazil: a systematic review and meta-analysis

Fração atribuível ao mofo habitacional nos casos de asma no Brasil: uma revisão sistemática e metanálise

Abstract

Background:  Asthma is one of the most common non-communicable diseases in the world. In Brazil, from 2017 to 2019, it was responsible for approximately 260 thousand hospitalizations, with R$ 149.3 million as direct costs and more than 817 thousand days of hospitalizations. Residential mold is an associated risk factor.

Objective:  Calculate cases of asthma attributable to the exposure to residential mold in Brazil.

Methods:  A meta-analysis was performed with studies from 2014 to 2019 selected by a systematic review in the Web Of Science and United States National Library of Medicine (PubMed) databases following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Residential mold is the exposure factor and asthma the outcome of interest. Quality analysis and publication bias followed the protocols of the Joanna Briggs Institute.

Results:  An association between residential mold and asthma was identified with a single odds ratio of 1.525 and a 95% confidence interval between 1.385 and 1.679. The fraction of asthma cases in Brazil attributable to exposure to residential mold was estimated to be 16.76%, which may result in 13,383 cases and 42,904 days of hospitalizations in 2019 in the public and complementary networks of the Brazilian health system.

Conclusions:  The study suggests that the mitigation of this risk factor could lead to a lower incidence of this outcome.

Keywords:
housing; fungi; asthma; systematic review; meta-analysis

Resumo

Introdução:  A asma é uma das doenças não transmissíveis mais comuns no mundo. No Brasil, de 2017 a 2019, foi responsável por aproximadamente 260 mil internações, R$ 149,3 milhões em custos diretos e mais de 817 mil dias de internações. O mofo habitacional é um fator de risco.

Objetivo:  Calcular os casos de asma atribuíveis à exposição ao mofo habitacional no Brasil.

Métodos:  Foi realizada uma metanálise com estudos publicados de 2014 a 2019 selecionados por revisão sistemática nas bases Web Of Science e United States National Library of Medicine (PubMed), seguindo as diretrizes Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). O mofo habitacional é o fator de exposição e a asma, o desfecho de interesse. A análise de qualidade e viés de publicação seguiu os protocolos do Joanna Briggs Institute.

Resultados:  Foi identificada uma associação entre mofo habitacional e asma com razão de probabilidade única de 1,525 e intervalo de confiança de 95% entre 1,385 e 1,679. A fração de casos de asma no Brasil atribuíveis à exposição ao mofo habitacional foi estimada em 16,76%, o que pode representar 13.383 casos e 42.904 dias de internações em 2019 nas redes pública e complementar do Sistema Único de Saúde.

Conclusões:  O estudo sugere que a mitigação desse fator de risco poderia ocasionar menor incidência desse desfecho.

Palavras-chave:
habitação; fungos; asma; revisão sistemática; metanálise

INTRODUCTION

Doctors and researchers in the field of public or collective health increasingly recognize the importance of social determinants of health, which include adequate housing. Several studies from around the world show the relationship between living in inadequate housing and its association with diseases, including respiratory diseases, asthma being one of the most prevalent¹–⁹.

Asthma is one of the most common non-communicable diseases, affecting approximately 339 million people of all ages in the world¹⁰, and in Brazil it is one of the most prevalent respiratory diseases, according to data from the Hospital Information System of the Brazilian Unified Health System (SUS), extracted from the Tabnet tool of the Department of Informatics of SUS (DATASUS). Between January 2017 and December 2019, asthma was responsible for approximately 260 thousand hospitalizations in the public and complementary networks of the SUS alone, excluding, therefore, data from the supplementary network, and corresponding to a direct cost of R$ 149.3 million and more than 817 thousand days of hospitalizations. It is worth noting that respiratory diseases, except tuberculosis, are not compulsory to report in Brazil, which may lead to underreporting. Besides, according to data from the SUS Hospital Information System, in the same period, there were more than 392 thousand hospitalizations with a total cost of more than 1.1 billion reais classified as Other Diseases of the Respiratory System, in the direct and complementary public health networks, including, for example, atelectasis or pulmonary collapse that can occur during the evolution of asthma¹¹.

Asthma has several risk factors, including genetic ones, environmental factors such as exposure to microorganisms and chemical elements, as well as psychosomatic, nutritional, and other factors, although its etiology is not firmly established. Therefore, it is considered that genetic predisposition is not the only indicator of susceptibility to this disease¹⁰,¹²–¹⁸.

In this sense, several previous studies have found evidence of the association between mold growth and moisture damage in residential environments and respiratory diseases, such as asthma and its symptoms⁴,⁸,⁹,¹⁹–²³. More recently, the World Health Organization (WHO)²⁴ confirmed that moisture and mold growth indoors are important risk factors in the prevalence of asthma and respiratory diseases.

The exact mechanisms by which moisture and mold affect the airways are not known, but signs of moisture, such as water leakage, visible mold, and others, are often associated with biological contaminants such as mites, mold, bacteria, in addition to the emission of volatile microbial organic compounds and chemicals due to the degradation of building materials⁹,¹⁹,²⁴,²⁵. Exposure to residential moisture and fungal contamination, for example, to common mold types such as Aspergillus, Alternaria, Candida, Cladosporium, Fusarium and Penicillium, has been associated in several studies with an up to twofold increased risk of asthma and wheezing, in addition to other predictive factors of mold contamination also being strongly associated with an increased risk of asthma and other respiratory diseases⁵,²⁴,²⁶.

Regarding the prevalence of exposure factors in homes, the literature demonstrates that the presence of dampness and mold in households is a common phenomenon worldwide. Although there is no gold standard for establishing the presence of moisture and residential mold, reports from the occupants of households or inspectors who check homes often report numbers in the magnitude of 10 to 50% in the most developed countries¹⁹,²⁴,²⁷–³¹. In Brazil, the magnitude of the problem is similar, with studies showing a prevalence sometimes higher than 50%³²–³⁶. Thus, it is understood that studies carried out in different locations around the world can be used for the Brazilian reality, since the incidence of the exposure factor of interest is prevalent in different latitudes.

This study hypothesizes that exposure to residential mold and/or moisture may be associated with a higher incidence of asthma when compared to the population not exposed to these risk factors. The objective of the present study was to perform a meta-analysis to analyze the association between exposure factors and the outcome of interest and, from that, to estimate the fraction that is attributable to exposure to mold and/or moisture in housing in the total number of cases and days of hospitalizations for asthma in public and complementary health systems in Brazil.

METHODS

This systematic review with meta-analysis was designed and conducted according to the guidelines in the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) checklist and the guidelines established in the Joanna Briggs Institute Reviewer's Manual. The review protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) database under number CRD42019145342.

We considered as primary inclusion criteria peer-reviewed studies, with a publication date of up to five years retrospectively to August 30, 2019. In addition, studies should have the odds ratio as a measure of association, controlled by confounding factors. Only studies made with primary data were accepted. Regarding the population of interest, studies with people of any age, gender, or country were selected. Observational studies, i.e., cross-sectional, cohort, and case-control studies, were also included.

Regarding the exposure of interest, the independent variable, the studies considered the presence of residential mold and/or moisture. In relation to outcome, the dependent variable, the studies considered reported cases of asthma and/or wheezing as outcomes in humans, either based on evaluations by health specialists or responses to questionnaires or interviews given by the occupants or guardians themselves.

The search was carried out on the United States National Library of Medicine (PubMed) and Web Of Science databases and, based on the identification of general and specific objectives and inclusion criteria, it used the Population, Exposition, Comparison, and Outcome (PECO) strategy, as established in the PRISMA checklist guidelines.

In searches by population, exposure, outcome, and measures of association, controlled Medical Subject Headings (MeSH) descriptors were used in addition to any related variations understood as applicable to this systematic review.

Regarding the population (P), the MeSH descriptor housing (Unique ID: D006798) and variations, such as search operators that identify their variations (*), such as residenc*, hous* and hom*, were used. These descriptors were chosen because the population of interest must live in residences.

Regarding exposures (E), terms that identified the presence of mold and/or moisture were included as descriptors. When inserting the term mold in the search for MeSH terms, that is, mold or mould, the search returned the term fungi (Unique ID: D005658). In turn, the term dampness did not generate results. Other possible variations such as moisture and leakage did not generate results either. However, given their relevance, they were also included along with search operators to identify variations (*).

As for comparison (C), no specific terms were included since the studies, to define effect sizes, already establish groups exposed and not exposed to risk factors.

Regarding the outcome (O), it was determined that they should be "asthma" and "wheezing". When inserting the term wheezing in the search for MeSH terms, the search returned respiratory sounds. The inclusion of wheezing is valid since some of the studies identify the presence of asthma from wheezing⁵,¹⁹,²²,³⁷–³⁹.

Terms that represent other outcomes related to respiratory diseases prevalent in Brazil were also included as descriptors, per the aforementioned DATASUS data, such as bronchitis and pneumonia. The inclusion of these is justified by the search strategy, that defines an outcome search only in the subject field, that is, in the titles and/or abstracts. Therefore, studies that did not present asthma and/or wheezing in the title and/or abstracts were excluded, but these outcomes of interest might be present throughout the text.

Thus, concerning the outcome, the following MeSH terms were used: asthma (Unique ID: D001249), respiratory sounds (Unique ID: D012135), pneumonia (Unique ID: D011014), bronchitis (Unique ID: D001991), respiratory tract diseases (Unique Id: D012140), all with search operators that identify their variations (*). Regarding the effect size, the MeSH term used was odds ratio (Unique ID: D016017). Search operators were also employed to locate any variations in writing. The search filter was structured to combine the descriptors selected using the Boolean operators AND/OR. The descriptors and the complete search strategies are mentioned below (Table 1).

Table 1
Search terms for United States National Library of Medicine (PubMed) and Web of Science and search strategies.

P - Population	E - Exposure	C - Comparison	O - Outcome	Effect Size
People of any age and country exposed to mold and associated risk factors in housing environments	Exposure to mold or risk factors associated with excess moisture or mold proliferation, such as water leaks, moisture, etc.	People not exposed to the mentioned risk factors	Asthma diagnosed by specialists or identified by other family members due to respiratory symptoms, such as wheezing and related symptoms.	Odds Ratio
MeSH terms, combined with Boolean operator "OR":	MeSH terms, combined with Boolean operator "OR":	MeSH terms, combined with Boolean operator "OR":	MeSH terms, combined with Boolean operator "OR":	MeSH terms, combined with Boolean operator "OR":
Housing (Unique ID: D006798)	Fungi (Unique ID: D005658)	N/A	Asthma (Unique ID: D001249)	Odds Ratio (Unique ID: D016017)
			Respiratory Sounds (Unique ID: D012135)
			Pneumonia (Unique ID: D011014)
			Bronchitis (Unique ID: D001991)
			Respiratory Tract Diseases (Unique Id: D012140)
Other variations (Not MeSH or MeSH with asterisk wildcard):	Other variations (Not MeSH or MeSH with asterisk wildcard):	Other variations (Not MeSH or MeSH with asterisk wildcard):	Other variations (Not MeSH or MeSH with asterisk wildcard):	Other variations (Not MeSH or MeSH with asterisk wildcard):
residen*	mold*	N/A	asthm*	odd*
hous*	mould*		pneumon*	ratio*
hom*	damp*		bronch*
	leakag*		respirat*
	moist*		wheez*
Search strategies
PubMed
((((((residenc*[Title/Abstract] OR hous*[Title/Abstract] OR hom*[Title/Abstract])) AND (asthm*[Title/Abstract] OR respirat*[Title/Abstract] OR bronchitis[Title/Abstract] OR pneumonia[Title/Abstract])) AND (fungi[Title/Abstract] OR mold*[Title/Abstract] OR mould*[Title/Abstract] OR damp*[Title/Abstract] OR moist*[Title/Abstract] OR leak*[Title/Abstract])) AND (odd*[Title/Abstract] AND ratio*[Title/Abstract])) AND ("2014/09/01"[Date - Publication] : "2019/09/01"[Date - Publication]))
Web Of Science
(ALL=(residen* OR hous* OR hom*) AND ALL=(asthm* OR respirat* OR bronchitis OR pneumonia) AND ALL=(fungi OR mold* OR mould* OR damp* OR moist* OR leakag*) AND ALL=(odd* AND ratio*)) AND DOCUMENT TYPES: (Article) Indexes=SCI-EXPANDED, SSCI, A&HCI, CPCI-S, CPCI-SSH, ESCI Timespan=Last 5 years

The initial screening of the records was carried out independently by two reviewers (ECN and COC) based on reading the titles and abstracts of the studies. Duplicate studies were removed by comparing authors, titles, journals, and year of publication (n=32). Studies not performed on humans (n=2) and meta-analyses (n=2) were also eliminated in the first screening.

After the initial screening, the recovery and reading of potentially relevant full texts were carried out. In this phase, all studies were submitted to eligibility analysis to identify those that met the requirements for systematic review. Eligibility was assessed independently by the authors and disagreements were resolved after discussion.

After reading all retrieved studies, those that did not fully meet all inclusion criteria were excluded. The first criterion for exclusion was articles without asthma and/or wheezing as the outcome (n=25). Then, studies without residential mold and/or moisture as exposure factors (n=15) were excluded. Finally, a study without the odds ratio as a measure of association was also excluded (n=1).

The review was carried out following the PRISMA guidelines, and the PRISMA tool was used to guide the process of review and synthesis of results. The PRISMA flowchart below describes search strategy and reasons for exclusions (Figure 1)⁴⁰.

Figure 1
Flowchart of the included studies.

Regarding the evaluation of methodological quality or critical appraisal, a process carried out in systematic reviews to establish the internal validity and the risk of bias in studies⁴¹, the critical appraisal tools for quantitative studies developed by the Joanna Briggs Institute were used.

After an initial selection by the authors, the entire texts were read and their methodological quality was evaluated according to the critical evaluation checklists of the Joanna Briggs Institute specific for each type of study. As three types of studies were returned in the searches and after the authors’ agreement—cross-sectional (n=14), cohort (n=5) and case-control (n=2)—, they were analyzed using three different checklists⁴².

To guarantee the quality of the analyzed evidence, only the studies that reached at least 70% of positive answers in the checklists were considered as having valid quality for inclusion in the meta-analysis and with a low risk of bias. Studies with positive responses between 50 and 69% should be considered at moderate risk of bias and still be subject to inclusion in the meta-analysis. Similar criteria have been previously adopted⁴³–⁴⁵.

From the accepted studies, information was extracted using a structured form based on the PECO strategy. The structured form followed the protocol for data extraction for systematic reviews of the etiology and risk of the Joanna Briggs Institute, which fully complies with the PECO strategy above⁴².

Consequently, a spreadsheet containing 23 fields for data extraction was defined, including the title of the study, authors, exposure of interest (independent variable), outcome of interest (dependent variable), study results (the measure of association), among others. After structuring the spreadsheet, a complete reading and data extraction was performed for the meta-analysis.

The measure of association used to synthesize the results of the selected studies was the odds ratio in the relationship between the main outcome, asthma (outcome) and exposure to risk factors, residential mold and/or moisture (exposure), after controlling for confounding factors.

The results were extracted and tabulated on the aforementioned spreadsheet. For studies with more than one odds ratio for the applicable risk factors, these odds ratios were summarized in just one, per study. To perform the aforementioned synthesis of all odds ratios and the subsequent meta-analysis, the generic inverse variance method was used using the MedCalc software (OSTEND; BELGIUM - VERSION 19.1.3). In this method, the measure of association and standard deviation are entered as natural logarithms in the software. The weight given to each study is chosen to be the inverse of the variance of the measure of association. Thus, larger studies, which have smaller standard deviations, receive more weight than smaller studies, which have larger standard deviations. This weight choice minimizes the imprecision or uncertainty of combined effect estimates⁴⁶.

RESULTS

Ninety-eight articles were initially identified in two databases, PubMed (n=40) and Web of Science (n=58). After applying the PRISMA flow, 36 articles were excluded in the analysis phase due to duplicity between the bases (n=32), not using primary data (n=2) or because they are not studies with humans (n=2). After the initial exclusion, 62 articles remained, which were fully accessed and evaluated in the eligibility analysis. Upon assessment of titles, abstracts, introductions and/or full texts, other studies were excluded (n=46) for the following reasons: having different outcomes than asthma and/or wheezing (n=25); not having residential mold and/or moisture as exposure factors (n=15); not presenting an odds ratio (n=1). Thus, 21 studies were selected for meta-analysis, 14 cross-sectional, five cohort and two case-control.

Out of these 21 studies, 11 were carried out with a population of young people or adults and ten with a population of children or adolescents. All articles were published between 2014 and 2019 (2014: n=2; 2015: n=4; 2016: n=4; 2017: n=4; 2018: n=1; 2019: n=6). The studies were carried out in 12 countries. All studies used multiple logistic regression models, adjusting for different types and quantities of confounding factors, all with 95% confidence intervals.

Regarding the type of measurement of the exposure factor, the majority of the studies were based on questionnaires (n=17). The others were based on: visual inspection (n=2); visual inspection and questionnaire (n=1); and laboratory test (n=1)

These measurements identified the presence of visible mold (n=18) as the most prevalent, followed by problems with the presence of water, such as leaks (n=9), the presence of odors, including mold or moisture (n=9), dampness in general (n=8), condensation on windows (n=5), damp bedding (n=2) and moisture on the floor (n=1). Some studies have, consequently, presented more than one type of exposure factor measurement. Besides, some have presented more than one measure of association for each type of exposure factor, whether by those who took the measurements, for example, inspector, researcher, or population, or also adjustments by confounding factors or other variables. In such a situation, a synthesis of the various results of the measures of association was performed to obtain a single measure per study.

Regarding the outcomes, most studies identified the presence of asthma only (n=12), using several different criteria, from self-reporting to answers in questionnaires such as the existence of asthma diagnosed by a doctor or other health professionals, use of asthma control drugs and even laboratory tests. The presence of asthma and wheezing was identified in eight other studies and wheezing alone in one study.

The analysis of quality and risk of bias in the studies was carried out using the critical appraisal checklists for studies of the Joanna Briggs Institute. All studies were considered for inclusion in the final systematic review, as they achieved positive responses above 70% in these lists, representing a low risk of bias⁴¹, and therefore were also included in the meta-analysis. The results of these checklists are shown below (Table 2).

Table 2
Joanna Briggs Institute Critical Appraisal Checklists for Different Types of Studies.

JBI Critical Appraisal Checklist for Cohort Studies
Question	Bjerg et al.38	Buckley and Carr12	Fu et al., 201659	Karvonen et al.4	Milanzi et al.22
Were the two groups similar and recruited from the same population?	YES	YES	YES	YES	YES
Were the exposures measured similarly to assign people to both exposed and unexposed groups?	YES	YES	YES	YES	YES
Was the exposure measured in a valid and reliable way?	UNCLEAR	YES	YES	YES	YES
Were confounding factors dentified?	YES	YES	YES	YES	YES
Were strategies to deal with confounding factors stated?	YES	YES	YES	YES	YES
Were the groups/participants free of the outcome at the start of the study (or at the moment of exposure)?	NO	NO	NO	YES	UNCLEAR
Were the outcomes measured in a valid and reliable way?	YES	YES	YES	YES	YES
Was the follow-up time reported and sufficient to be long enough for outcomes to occur?	YES	NOT APPLICABLE	YES	YES	YES
Was follow-up complete, and if not, were the reasons to loss of follow-up described and explored?	YES	NOT APPLICABLE	YES	YES	YES
Were strategies to address incomplete follow-up utilized?	NOT APPLICABLE	NOT APPLICABLE	NOT APPLICABLE	NOT APPLICABLE	NOT APPLICABLE
Was appropriate statistical analysis used?	YES	YES	YES	YES	YES
OVERALL APPRAISAL:	INCLUDE	INCLUDE	INCLUDE	INCLUDE	INCLUDE

JBI Critical Appraisal Checklist for Case Control Studies
Question	Oluwole et al.14	Shorter et al.8
Were the groups comparable other than the presence of disease in cases or the absence of disease in controls?	YES	YES
Were cases and controls matched appropriately?	YES	YES
Were the same criteria used for identification of cases and controls?	YES	YES
Was exposure measured in a standard, valid and reliable way?	YES	YES
Was exposure measured in the same way for cases and controls?	YES	YES
Were confounding factors identified?	YES	YES
Were strategies to deal with confounding factors stated?	YES	YES
Were outcomes assessed in a standard, valid and reliable way for cases and controls?	YES	YES
Was the exposure period of interest long enough to be meaningful?	YES	YES
Was appropriate statistical analysis used?	YES	YES
OVERALL APPRAISAL:	INCLUDE	INCLUDE

JBI Critical Appraisal Checklist for Analytical Cross Sectional Studies
Question	Ahlroth Pind et al.19	Barreto and Sole37	Cai et al.2	Eiffert et al.3	Eriksson et al.38	Lam et al.13	Lanthier-Veilleux et al.27	Moses et al.5	Olaniyan et al.21	Sharpe et al.26	Takaoka et al.23	Wang et al.9	Weber et al.16	Zhang et al.18
Were the criteria for inclusion in the sample clearly defined?	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES
Were the study subjects and the setting described in detail?	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES
Was the exposure measured in a valid and reliable way?	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES
Were objective, standard criteria used for measurement of the condition?	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES
Were confounding factors identified?	YES	UNCLEAR	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES
Were strategies to deal with confounding factors stated?	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES
Were the outcomes measured in a valid and reliable way?	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES
Was appropriate statistical analysis used?	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES
OVERALL APPRAISAL:	INCLUDE	INCLUDE	INCLUDE	INCLUDE	INCLUDE	INCLUDE	INCLUDE	INCLUDE	INCLUDE	INCLUDE	INCLUDE	INCLUDE	INCLUDE	INCLUDE

Overall, the review identified a significant association in 18 of the 21 studies between exposure factors, i.e., residential mold and/or moisture, and the outcomes of interest, i.e., asthma and/or wheezing. The association is considered significant if the odds ratio is greater than 1.

After obtaining a single combined odds ratio per each study, a single combined association measure, i.e., a single odds ratio was obtained from all studies approved. The final odds ratio was clustered in one final measure of association by the random-effects model. This model considers that the true effects in the studies vary between studies and the clustering measure is the weighted average of the effects reported in the different studies. This model tends to return more conservative results and should be the preferred model for use when the results are heterogeneous. In this study, the I² value in the heterogeneity test was 66.93%, indicating the presence of a moderately high heterogeneity⁴⁷,⁴⁸.

Therefore, the single odds ratio, derived from clustering all studies, was 1.525, with a confidence interval of 1.385 to 1.679 and a p-value<0.001 (Table 3). Thus, it was identified that the risk of asthma or wheezing is higher among those exposed to residential mold and/or moisture (risk factors) than among those not exposed.

Table 3
Odds ratios grouped by study. with confidence intervals. p-value and weight randomly assigned to each study by the generic inverse variance method. and final odds ratio from all studies with confidence intervals and p-value.

Id	Authors	Publishing year	Odds Ratio (adjusted)	Confidence Interval (95%)		p-value	Weight (%) Random
4	Eiffert et al.3	2016	0.820	0.300	2.260	0.690	0.82
5	Milanzi et al.22	2019	0.974	0.575	1.648	0.920	2.51
6	Eriksson et al.39	2015	1.379	1.053	1.806	0.019	5.60
7	Shorter et al.8	2018	1.824	1.566	2.125	<0.001	8.07
8	Buckley and Carr12	2017	2.250	1.280	3.980	0.005	2.25
9	Ahlroth Pind et al.19	2017	1.325	1.222	1.438	<0.001	9.61
11	Lanthier-Veilleux et al.27	2016	1.725	1.481	2.009	<0.001	8.07
14	Wang et al.9	2019	1.495	1.320	1.694	<0.001	8.90
15	Cai et al.2	2019	1.371	1.196	1.572	<0.001	8.50
16	Olaniyan et al.21	2019	1.550	0.911	2.637	0.106	2.51
17	Karvonen et al.4	2015	1.546	1.054	2.267	0.026	3.80
18	Bjerg et al.38	2015	1.466	1.022	2.104	<0.001	4.32
24	Weber et al.16	2017	1.769	1.234	2.535	0.002	4.32
25	Fu et al., 201659	2016	3.773	1.862	7.647	<0.001	1.58
29	Sharpe et al.26	2015	1.854	1.407	2.444	<0.001	5.60
30	Oluwole et al.14	2017	2.234	1.255	3.978	0.006	2.25
46	Lam et al.13	2014	2.560	1.400	4.680	<0.05	2.02
48	Moses et al.5	2019	1.445	0.815	2.562	0.208	2.25
55	Takaoka et al.23	2016	1.185	0.892	1.574	0.243	5.60
61	Barreto and Sole37	2014	1.800	1.100	3.200	0.024	2.51
62	Zhang et al.18	2019	1.140	1.020	1.274	0.021	8.90
Total (random effects)			1.525	1.385	1.679	<0.001

The forest plot of the 21 studies, already pooled individually by the random-effects model, and also with its final measure of association, with its respective confidence interval, is shown below (Figure 2).

Figure 2
Forest plot for the meta-analysis of the studies grouped by the generic inverse variance method with random effects.

The final measure of association, the single odds ratio, can be interpreted as the incidence of asthma or wheezing 1.525 times higher for the group exposed to the risk factors compared to the group without such exposure. Thus, it is also possible to interpret that exposure to risk factors, that is, residential mold and/or moisture, increases the incidence of asthma or wheezing, the outcomes of interest in this study.

Likewise, it is also possible to infer that, by not being exposed to the risk factors of interest in this study, a part of the cases of asthma or wheezing would be avoided. The difference between 1 and 1.525 can be interpreted as the preventable cases of asthma or wheezing if there was no exposure to residential mold and/or moisture, even after controlling for confounding factors.

Prevalence of mold and/or moisture in Brazilian households and calculation of the fraction attributable to the exposure factors in cases of asthma in Brazil

No study identifying the incidence of mold and/or moisture in Brazilian households in a country level was found. However, some studies show the prevalence of residential mold and/or moisture in specific locations. Bresolini et al.³², in a study carried out in 2016 in Belo Horizonte, Minas Gerais, recorded the presence of visible mold in 27 of the 87 homes visited (31.0%). In another study on the presence of mold in the homes of newborns in the city of São Paulo, Fiório³³ reports that 250 residences showed visible mold among the 377 residences observed (66%). Guarato³⁴, in a study carried out in Ribeirão Preto, São Paulo, reported that 21.1% of the 3,167 participants declared the presence of mold in their homes. In another study using the International Study of Asthma and Allergies in Childhood (ISAAC) questionnaire with 580 students from Guarulhos, São Paulo, Pendloski³⁵ pointed out that 57.6% of the houses presented mold stains. Pineda³⁶, in a study in Salvador, Bahia, identified the presence of moisture or mold on the walls in the homes of 841 children (64.1%).

Thus, weights were applied to prevalence and sample sizes. The result obtained was a 38.4% prevalence of residential mold and/or moisture, the risk factors of interest (independent variable).

To calculate the fraction of asthma cases (dependent variable) attributable to the exposure to residential mold and/or moisture (independent variable), the concept of attributable risk was used. This concept, presented in several studies³¹,⁴⁹,⁵⁰, is defined as the proportion of cases of the outcome of interest that can be attributed to the exposure and can be formally written, based on Bayes’ Theorem, according to Benichou⁵¹, as the Equation 1:

(1) $$\text{AF}=\left[\text{P}\left(\text{RR-}1\right)\right]/\left[\text{P}\left(\text{RR-}1\right)+1\right]$$

In this equation, AF is the attributable fraction, P is the prevalence of the risk factor (residential mold and/or moisture) and RR is the relative risk of exposure (risk ratio in the exposed population in comparison to the unexposed population).

The odds ratio was the measure of association used to replace the relative risk, considering that it can be used instead of the relative risk because it represents a reasonable approximation in a study in which the prevalence of the outcome of interest is low, that is, lower than 15%³¹,⁵⁰. The identified and consolidated prevalences were 13.8% for active asthma and 7.0% for asthma with a medical diagnosis in Brazil, based on data weighted by the sample sizes extracted from several studies carried out in Brazil—ISAAC, National School Health Survey (PeNSE), Study of Cardiovascular Risks in Adolescents (ERICA), WHO World Health Survey, National Health Survey³⁷,⁵²–⁵⁴. The risk estimate for exposure to residential mold and/or moisture was derived from the meta-analysis carried out in this study. As mentioned above, the meta-analysis returned an odds ratio of 1.525 in the association between the outcome of interest, i.e., asthma and/or wheezing, and the exposure factor, i.e., residential mold and/or moisture. Thus, when using this odds ratio and the prevalence of mold and/or dampness of 38.36%, the estimate of the fraction of asthma cases attributable to exposure to mold and/or moisture in housing was estimated according to the Equation 2:

(2) $$\text{AF}=\left[0.3836*\left(1.525\text{-1}\right)\right]/\left[\mathrm{0.3836*}\left(1.525\text{-}1\right)+1\right]\text{-}>\text{AF}=16.76\%$$

Therefore, the fraction of asthma cases in Brazil attributable to exposure to residential mold and/or moisture can be estimated to be 16.76%. Consequently, in 2019, the cases of hospitalization for asthma in the public and complementary health networks in Brazil that were attributable to exposure to residential mold and/or moisture in housing were estimated to be 13,383, representing 42,904 days of hospitalization. These numbers may vary since asthma is a multifactorial disease and the presence of residential mold and/or moisture may trigger asthma symptoms in some circumstances but not in others. Other well-known factors can also play a role in triggering asthma symptoms or even protecting from them¹⁰,¹²–¹⁸. It is worth mentioning that, in December 2019, the public and complementary networks of the Brazilian health system registered 66.7% of hospitalization and complementary beds in the country. The private network not affiliated to SUS, the supplementary health system, held the remaining 33.3%.

Study limitations

The data collected from the studies showed that housing and health elements are associated, but this association may not be necessarily causal. Also, it is not possible to exclude the possibility of reverse causality⁵⁵.

Most of the 21 studies included in this systematic review are cross-sectional (n=14) or cohort with few follow-up periods (n=5). From these, almost all data on exposure to residential mold and/or moisture and also on the outcome, asthma and/or wheezing, are based on responses to questionnaires applied to the occupants or guardians themselves. These responses can be more subjective and therefore more inaccurate and subject to bias than home inspections carried out by trained civil engineers or data from medical reports. Also, studies have shown that there is no established standard method for measuring mold and moisture for use in epidemiological studies. Thus, studies have used several ways to identify this measurement, each with advantages and disadvantages. Thus, responses to questionnaires can lead to artificial associations between mold and/or moisture in housing and adverse health effects, especially in cross-sectional studies²,⁴,⁸.

Sandel and Wright¹⁷ point out that research studies on housing suggest that environmental exposures to mites, mold, dampness, cockroaches, and others, very well known in this area, do not completely explain the trends of asthma or disparities observed in the expression of the disease. This leads to the consideration that factors not yet fully identified may play a role. At the same time, mechanisms that connect psychological stress, negative affections and emotions with atopic disorders, including asthma, are being increasingly elucidated. Thus, research that includes psychological, psychosomatic, and other issues in this dimension can contribute to the definition of the etiology of asthma.

Regarding geography, it is clear that almost all studies were carried out outside Brazil. Although evidence was found of the feasibility of using these studies for other latitudes, validating the use of the data for the reality of Brazil, it is important that further research on the association between exposure factors and outcomes used in this study are carried out in Brazil.

Another limitation is that there are different levels of severity of asthma. Rabe et al., in a study with subjects from Western and Eastern Europe, Japan, Asia-Pacific and the US, found that 18% of the people face severe, 20% persistent, 18.1% mild and 43.9% intermittent asthma⁵⁶. Thus, it would be important to identify the relationship between these specific groups and the exposure factor studied herein to calculate the impact on the number and days of hospitalizations.

DISCUSSION

The findings of this research are in line with other studies. Mudarri and Fisk estimate the proportion of U.S. current asthma cases that are attributable to dampness and mold exposure at 21%. These authors state that, of the 21.8 million people reported to have asthma in the U.S., approximately 4.6 (2.7–6.3) million cases are estimated to be attributable to dampness and mold exposure in the home. These authors state that this situation represents a substantial public health impact that could be avoided with policies and programs designed to prevent or mitigate mold and dampness in residencies³¹. Jaakkola et al.⁵⁷ estimated the fraction of asthma attributable to workplace mold exposure to be 35.1% among the exposed, in a Finnish study. In a research carried out in Taiwan, Lee et al.⁵⁸ concluded that indoor factors, i.e., the presence of water damage, visible mold or the presence of cockroaches accounted for 16,500 excess cases of asthma out of the estimated 195,300 cases of physician-diagnosed asthma in 6- to 15-year-old Taiwanese elementary- and middle-school children.

Thus, our findings suggest that housing environments free from mold and moisture have the potential to significantly contribute to improving the health and well-being of the population, with possible positive and relevant impacts on the incidence of asthma in Brazil and its direct and indirect consequences.

The detailed evidence of this systematic review with meta-analysis, followed by an estimate of an attributable factor of the exposure to residential mold and/or moisture in the cases of asthma and/or wheezing, can contribute to providing information for the development of health promotion and prevention interventions. Besides, it can provide subsidies for public interventions, especially concerning the assessment of housing construction standards in Brazil and the issue of housing supply itself, especially for groups most vulnerable to the exposure factors or even those who already have the outcome of interest. Also, the research, based on the results presented, can serve for public health managers and even other stakeholders to revisit the importance of the housing issue as part of public and collective health. Especially, the research can contribute information that leads to the creation of actions aiming at reducing the incidence of mold and moisture first for groups that already present asthma and wheezing, and, later, as measures of promotion and prevention healthcare for broader groups of the population.

CONCLUSION

The fraction of asthma cases in Brazil attributable to exposure to residential mold and/or moisture can be estimated to be 16.76%. Thus, in 2019, cases of hospitalization for asthma in the public and complementary health networks in Brazil attributable to exposure to mold and/or moisture in housing were estimated to be 13,383, representing 42,904 days of hospitalization. These numbers may vary since asthma is a multifactorial disease and the presence of residential mold and/or moisture may trigger asthma symptoms in some circumstances but not in others. Therefore, the determination of a fraction attributable to this exposure in cases of asthma suggests that the elimination of these risk factors could lead to a lower incidence of this outcome, representing potential savings to the health system and improvements in the quality of life of millions of Brazilians.

• Funding:
  Coordination for the Improvement of Higher Education Personnel - Brazil (CAPES) - Financing Code 001.

ACKNOWLEDGMENTS

The authors would like to thank the researcher Cristina Oliveira de Carvalho for her collaboration in the initial phase of selection and reading of the articles.

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Publication Dates

• Publication in this collection
  07 Apr 2025
• Date of issue
  2025

History

• Received
  10 Sept 2021
• Accepted
  16 July 2022