Effect of Damp and Mold Affected Housing on Mental Health - Mold Inspection, Assessment, & Testing Services

A recent article published in Environmental Health Perspectives (Volume 132, Issue 8, August 2024) discussed the Effect of Damp and Mold Affected Housing on Mental Health. This review study found positive associations between residential dampness/mold exposure and poor mental health. The authors call for further study of the psychosocial and physiological mechanisms by which mold exposure may influence mental health.

The article can be found on their website at https://ehp.niehs.nih.gov/doi/10.1289/EHP14341 as well as below.

A State-of-the-Science Review of the Effect of Damp- and Mold-Affected Housing on Mental Health

Authors: Maria Rosa Gatto https://orcid.org/0009-0007-0974-4793, Adelle Mansour, Ang Li, and Rebecca Bentley Authors Info & Affiliations

Publication: Environmental Health Perspectives

Volume 132, Issue 8

CID: 086001

https://doi.org/10.1289/EHP14341

Abstract

Background:

While it is well-established that exposure to dampness or mold in homes negatively affects physical health, the association with mental health remains less well evidenced. As plausible psychosocial and biological pathways exist between dampness and mold exposure and poor mental health, a review of evidence is required.

Objective:

This State-of-the-Science review sought to assess what is known about the mental health effects of dampness or mold exposure and identify gaps in the literature and priorities for further research.

Methods:

A comprehensive search of electronic databases (MEDLINE, Embase, PsycInfo, Global Health, Web of Science, and Scopus) was conducted to identify relevant studies published from 2003 to 2023. Eligible studies included observational study designs such as cohort and cross-sectional studies. Target studies for review assessed the effect of dampness and/or mold on mental health outcomes.

Results:

Of the 1,169 records retrieved, 19 studies met the inclusion criteria. The available evidence described positive associations between residential dampness/mold exposure and poor mental health. In adults, associations were observed for outcomes such as depression, stress, and anxiety, while for children, associations were observed for emotional symptoms and emotional dysregulation.

Discussion:

Identified studies generally reported associations between exposure to dampness/mold in the home and poorer mental and emotional health. Given the methodological limitations present in the current evidence base, it is recommended that more research be conducted. https://doi.org/10.1289/EHP14341

Introduction

The World Health Organization (WHO) guidelines on indoor air quality emphasize that mold exposure poses a significant risk to human health.¹ The prevalence of mold growth in dwellings varies between countries, but estimates range between 10% and 50%.¹ Due to the prevalence and the health risks it poses, WHO recommends that indoor mold growth should be prevented and remediated as a priority.¹ Given that climate change is anticipated to likely increase human exposure to poor indoor air quality,² adverse climatic conditions,³ and natural disasters such as flooding,⁴ it is imperative that we understand the impacts of the subsequent mold growth that is likely to occur. The adverse effects associated with mold exposure on physical health are well-documented and include asthma,⁵ allergic symptoms and rhinitis,^6,7 dermatitis,⁸ fatigue,⁸ sleep problems,⁹ headache,⁸ and sore throat.⁸ Plausible pathways have also been identified between adverse housing conditions and poor mental health through residential dissatisfaction and psychosocial stress, which may be improved through remediation of the structural factors that cause the housing conditions in question.^10,11

Evidence exists that suggests that people’s physical living conditions—including those related to the likely presence of mold and dampness—are directly and indirectly associated with mental health.¹² Examples of such living conditions include poor-quality housing,¹³ low indoor temperatures,¹⁴ and persistent poor housing conditions.¹⁵ Structural housing problems have been shown to be related to suicidal ideation.^16,17 There is also evidence that some people are more vulnerable to negative mental health effects associated with poor housing conditions. For example, lack of autonomy to fix housing problems for people in the rental sector has been shown to exacerbate existing depressive symptoms attributable to poor housing conditions.¹⁵ Low income households may be more vulnerable to experiencing negative mental health effects: the financial strain from remediating homes affected by mold and dampness may negatively impact their mental health.¹⁵ Indeed, the costs of fixing water damage and remediating mold are among the most costly repairs to property.¹⁸ Adding further complexity, Kearns et al.¹⁹ theorize that, above all else, the presence of structural problems within homes counteracts any psychosocial benefits homes provide.

While most theories on the underlying cause of residential mold exposure on mental health draw on psychosocial explanations, physiological mechanisms are also possible. Biomarkers have been associated with poor mental health.²⁰ For example, pro-inflammatory markers have been found to be higher in people living with depression.²¹ Additionally, the hypothalamic–pituitary–adrenal (HPA) axis may be overactive in individuals with depression and/or chronic stress.^22,23 Other biomarkers that may be implicated in poor mental health include c-reactive protein,²⁴ cortisol,²⁵ and serotonin.²⁶ While the link between biomarkers and mental health has been studied, the physiological effects of mold exposure on biomarker activity and mental health remain speculative, as very few studies have been conducted in the field.

Despite the clear need to understand how residential mold and dampness affect mental health, few reviews have examined the relationship, apart from one on adverse living conditions and depressive mood.²⁷ Most extant reviews have focused on specific physical health conditions, such as asthma and allergic symptoms.^28,29 To address this gap in evidence, we conducted a State-of-the-Science review of published research examining the association between exposure to dampness and mold in homes and mental health outcomes. For the purpose of this review, we define mental health in terms of symptoms related to emotional, psychological, and social wellbeing. This review has two main aims:

1. Synthesize existing evidence on the association between residential mold exposure and mental health

2. Identify gaps in the literature and opportunities for future research.

Methods

A State-of-the-Science review approach was undertaken to enable article selection, data extraction, and narrative synthesis across quantitative studies to gain a comprehensive understanding of the topic and fulfil the research aims.

Eligibility Criteria

Study characteristics.

The review includes empirical papers using observational study designs, including cohort studies, case-control studies, case-crossover studies, and cross-sectional studies. Simulation and modeling studies were excluded since their aims are to evaluate methods rather than ascertain an association, as were reviews and qualitative studies, since this review focuses solely on the quantitative literature.

Population.

All human populations. There was no restriction on age of study participants or study location.

Exposure.

The presence of mold and/or dampness in a residential setting. Examples of eligible exposures included those measured by visible mold, square feet of mold, and indoor dampness. Examples of ineligible exposures included indirect measures such as level of satisfaction with control over the presence of dampness or mold, composite measures of water damage which do not overtly separate dampness or mold from other indicators (such as changes to the structural integrity of the building, burst pipes, flooding, etc.), and composite measures of housing conditions that included but were not limited to dampness and mold.

Outcomes.

Doctor-diagnosed and self-reported measures of mental health in terms of emotional, psychological, and social wellbeing. For example, depression or depressive symptoms, anxiety, stress, and posttraumatic stress (PTS), emotional symptoms, and self-reported mental health. All other health outcomes, including physical health, subjective measures of wellbeing that encompass both physical and mental health, neurodevelopmental conditions, and mental health outcomes not related to mood (such as substance use disorders, eating disorders, and psychotic disorders) were excluded to narrow the scope of the review. In addition, if the outcome of interest was measured but results were not reported in the paper, the study was excluded from consideration.

Report characteristics.

We restricted our analysis to peer-reviewed research articles. All other publication types, including abstracts, conference proceedings, unpublished studies, protocols, opinion pieces, and gray literature, were excluded. Publication dates were restricted to articles published in the past 20 years, from 2003 onwards. Only studies available in English were included.

Information Sources

A research librarian at the authors’ institution was consulted for input on database selection and search terms. On 25 April 2023, M.R.G. searched MEDLINE (OVID Technologies, 1946 to present), Embase (OVID Technologies, 1947 to present), PsycInfo (OVID Technologies, 1806 to present), Global Health (CAB International, 1973 to present), Web of Science (Clarivate, 1900 to present), and Scopus (Elsevier, 1788 to present). On 11 May 2023, the reference lists of included papers were hand searched for other eligible papers, and cited reference searches were conducted in Google Scholar for each included paper. Searches were rerun on 18 and 19 September 2023 with a date restriction of 2023–present to confirm that newer studies were not omitted.

Search Strategy

The full line by line search as run in each database can be found in Table S1. Candidate search terms were based around the three main themes (mold, housing, and mental health). Relevant synonyms for each term were included to allow for a comprehensive search. The search strategy was piloted by M.R.G., who validated the sensitivity of the search strategy by testing its effectiveness in identifying known relevant studies.

Selection Process

Study selection was conducted using the review management platform Covidence (Veritas Health Innovation). Two researchers (M.R.G. and A.M.) independently reviewed titles and abstracts of the records identified by database searches. In case of disagreement, consensus on which articles to send to full-text screening was reached by discussion. If necessary, a third researcher (A.L. or R.B.) was consulted to make the final decision. Screening criteria were left broad at the title and abstract stage to ensure that no relevant article was inadvertently omitted. Next, two researchers (M.R.G. and A.M.) independently screened the full-text articles for inclusion. Again, in case of disagreement, consensus was reached on inclusion or exclusion by discussion and, if necessary, consultation with a third researcher (A.L. or R.B.).

Data Items

We collected data on:

• The report: author, year, source of publication, study funding source, reported conflicts of interest

• Population and setting: data source, population description, study setting, inclusion criteria, exclusion criteria, method of recruitment, whether informed consent was obtained, and length of follow-up

• Methods: study aims and objectives, study design, start date, end date

• Exposure: definition, measurement method, measurement tool, whether the measurement tool was validated

• Outcome: definition, measurement method, measurement tool, whether the measurement tool was validated

• Statistical analysis: software used, statistical methods, missing data strategy, confounding factors adjusted for in analysis

• Baseline characteristics: total number of participants, response/participation rate, withdrawals/exclusions/loss to follow-up, age, sex, race/ethnicity, participants with mold/dampness, participants with outcome, other relevant sociodemographic information, baseline imbalances

• Results: univariate associations, multivariate associations, measures of precision (e.g., 95% confidence intervals, 𝑝-values)

• Study conclusions

We anticipated that individual studies may report data for multiple mental health outcomes. Specifically, a single study may report results:

• for multiple constructs related to mood or mental health, for example, stress and anxiety;

• that use multiple methods or tools to measure the same or similar outcome; and

• for outcome measures at multiple time-points.

Where multiple mental health outcomes or outcomes measured at different time points were reported by the same paper, all outcomes were included and analyzed.

Data Extraction and Synthesis

Data extraction was conducted using a data extraction form created in Covidence. One reviewer (M.R.G.) independently extracted data from each report. Completed data extraction forms were then checked for accuracy by a second reviewer (A.M.). As in study selection, consensus was reached by discussion and consultation of a third reviewer (A.L. or R.B.) where necessary. Where multiple papers corresponded to the same study, all data was extracted separately for each report so inconsistencies and discrepancies could be considered during synthesis. A systematic review with meta-analysis was not feasible due to the expected substantial methodological and statistical heterogeneity between included papers. Instead, a narrative synthesis was undertaken whereby findings were presented within the following descriptive themes: study characteristics, dampness and mold assessment, factors that impact the likelihood of exposure to dampness and mold, mental health assessment, mental health effects in adults, mental health effects after flooding, mental health effects in parents, and mental health effects in children.

Results

The PRISMA flow diagram (Figure S1) outlines the literature screening process. Database searches yielded a total of 1,169 entries. After removal of duplicates, the titles and abstracts of 614 unique records were independently screened. Of these, 59 full texts were reviewed, and 42 were excluded. The main reasons for exclusion were the incorrect exposure, incorrect outcome, and wrong publication type. After searching the reference lists of included studies and searching for papers that cited the 17 included studies, two additional papers were included. Nineteen papers associated with 17 separate studies were included in the final dataset.^30–48

Study Characteristics

An overview of the included studies’ characteristics is found in Tables 1 and 2. Multiple research study designs were used to evaluate the effect of exposure to damp or mold-affected housing on mental health. Most were cross-sectional studies (𝑛=12, 63%),^{30–34,37,38,44–48} followed by cohort studies (𝑛=5, 26%)^{35,36,41–43} and case-control studies (𝑛=2, 11%).^39,40 The case-control studies used self-selected case series of symptomatic individuals who reported mold exposure (confirmed with mold sampling) compared with asymptomatic community controls.^39,40 Most of the studies (𝑛=10, 53%) had a relatively large sample size (i.e., more than 1,000).^{32,33,35–37,41–43,47,48} Regarding geographical distribution, a large proportion of papers were specific to the US (𝑛=6, 32%),^{34,38–40,44,48} and UK (𝑛=4, 21%),^37,41–43 followed by New Zealand (𝑛=2, 11%).³² One paper each was specific to China,³³ Sweden,⁴⁵ Denmark,³⁶ Germany,³⁵ Guyana,³⁰ and Japan,³¹ while one paper was a multicenter Europe-based paper.⁴⁷ Mental health was measured using self-reported measures, either surveys or screening tools, in all but one study,³⁶ which used data linkage to the Danish National Patient Register. Exposure definitions encompassed dampness and/or mold, measured by self-report or independent assessment. In the included papers, the demographics of the study population varied by different life contexts and health statuses (i.e., children, adults, parents, residents of recently flooded areas, immigrants, social housing residents, individuals with asthma, minority populations).

Table 1 Summary of the characteristics of existing papers (𝑛=19) that analyze the effect of residential dampness and/or mold exposure on measures of mental health.

Variable	Categories of variable	𝑛 (%)	Reference(s)
Mental health definition	Depression or depressive symptoms	4 (21.1%)	Akpinar-Elci et al.,³⁰ Kilburn,^39,40 Shenassa et al.⁴⁷
	Parental mental health outcomes	3 (15.8%)	Butler et al.,³² Groot et al.³⁶
	Stress and posttraumatic stress	3 (15.8%)	Flores et al.,³⁴ Oluyomi et al.,⁴⁴ Oudin et al.⁴⁵
	Mental health	2 (10.5%)	Chen et al.,³³ Wen and Balluz⁴⁸
	Emotional dysregulation	2 (10.5%)	Mueller and Flouri,⁴² Oloye and Flouri⁴³
	Emotional symptoms	2 (10.5%)	Casas et al.,³⁵ Midouhas et al.⁴¹
	Multiple mental health outcomes	3 (15.8%)	Azuma et al.,³¹ Huebner et al.,³⁷ Kang et al.³⁸
Method of data collection of mental health variable	Validated survey tool	13 (68.4%)	Akpinar-Elci et al.,³⁰ Butler et al.,³² Chen et al.,³³ Flores et al.,³⁴ Casas et al.,³⁵ Kang et al.,³⁸ Kilburn,^39,40 Midouhas et al.,⁴¹ Mueller and Flouri,⁴² Oloye and Flouri,⁴³ Paterson et al.,⁴⁶ Shenassa et al.⁴⁷
	Nonvalidated survey tool	5 (26.3%)	Azuma et al.,³¹ Huebner et al.,³⁷ Oluyomi et al.,⁴⁴ Oudin et al.,⁴⁵ Wen and Balluz⁴⁸
	Health registries	1 (5.3%)	Groot et al.³⁶
Exposure under study	Mold	10 (52.6%)	Akpinar-Elci et al.,³⁰ Chen et al.,³³ Flores et al.,³⁴ Casas et al.,³⁵ Groot et al.,³⁶ Kilburn,^39,40 Oluyomi et al.,⁴⁴ Oudin et al.,⁴⁵ Wen and Balluz⁴⁸
	Dampness	6 (31.6%)	Azuma et al.,³¹ Huebner et al.,³⁷ Midouhas et al.,⁴¹ Mueller and Flouri,⁴² Oloye and Flouri,⁴³ Paterson et al.⁴⁶
	Mold and dampness	3 (15.8%)	Butler et al.,³² Kang et al.,³⁸ Shenassa et al.⁴⁷
Method of data collection of exposure variable	Validated survey tool	2 (10.5%)	Akpinar-Elci et al.,³⁰ Chen et al.³³
	Nonvalidated survey tool	13 (68.4%)	Azuma et al.,³¹ Butler et al.,³² Flores et al.,³⁴ Casas et al.,³⁵ Groot et al.,³⁶ Huebner et al.,³⁷ Kang et al.,³⁸ Midouhas et al.,⁴¹ Mueller and Flouri,⁴² Oloye and Flouri,⁴³ Oluyomi et al.,⁴⁴ Paterson et al.,⁴⁶ Wen and Balluz⁴⁸
	Independent assessment	1 (5.3%)	Oudin et al.⁴⁵
	Survey and independent assessment	3 (15.8%)	Kilburn,^39,40 Shenassa et al.⁴⁷
Geographic region	Europe	8 (42.1%)	Casas et al.,³⁵ Groot et al.,³⁶ Huebner et al.,³⁷ Midouhas et al.,⁴¹ Mueller and Flouri,⁴² Oloye and Flouri,⁴³ Oudin et al.,⁴⁵ Shenassa et al.⁴⁷
	North America	6 (31.6%)	Flores et al.,³⁴ Kang et al.,³⁸ Kilburn,^39,40 Oluyomi et al.,⁴⁴ Wen and Balluz⁴⁸
	South America	1 (5.3%)	Akpinar-Elci et al.³⁰
	Asia	2 (10.5%)	Azuma et al.,³¹ Chen et al.³³
	Oceania	2 (10.5%)	Butler et al.,³² Paterson et al.⁴⁶
Context	Normal life	15 (78.9%)	Butler et al.,³² Chen et al.,³³ Casas et al.,³⁵ Groot et al.,³⁶ Huebner et al.,³⁷ Kang et al.,³⁸ Kilburn,^39,40 Midouhas et al.,⁴¹ Mueller and Flouri,⁴² Oloye and Flouri,⁴³ Oudin et al.,⁴⁵ Paterson et al.,⁴⁶ Shenassa et al.,⁴⁷ Wen and Balluz⁴⁸
	Natural disaster	4 (21.1%)	Akpinar-Elci et al.,³⁰ Azuma et al.,³¹ Flores et al.,³⁴ Oluyomi et al.⁴⁴
Population age group	Adults	14 (73.7%)	Akpinar-Elci et al.,³⁰ Azuma et al.,³¹ Butler et al.,³² Chen et al.,³³ Flores et al.,³⁴ Groot et al.,³⁶ Huebner et al.,³⁷ Kang et al.,³⁸ Kilburn,^39,40 Oluyomi et al.,⁴⁴ Paterson et al.,⁴⁶ Shenassa et al.,⁴⁷ Wen and Balluz⁴⁸
	Children	5 (26.3%)	Casas et al.,³⁵ Midouhas et al.,⁴¹ Mueller and Flouri,⁴² Oloye and Flouri,⁴³ Oudin et al.⁴⁵
Sample size	≤100	1 (5.3%)	Kang et al.³⁸
	101–500	7 (36.8%)	Akpinar-Elci et al.,³⁰ Azuma et al.,³¹ Flores et al.,³⁴ Kilburn,^39,40 Oluyomi et al.,⁴⁴ Oudin et al.⁴⁵
	501–1,000	1 (5.3%)	Paterson et al.⁴⁶
	1,001–5,000	2 (10.5%)	Butler et al.,³² Casas et al.³⁵
	5,001–10,000	2 (10.5%)	Chen et al.,³³ Shenassa et al.⁴⁷
	>10,000	6 (31.6%)	Groot et al.,³⁶ Huebner et al.,³⁷ Midouhas et al.,⁴¹ Mueller and Flouri,⁴² Oloye and Flouri,⁴³ Wen and Balluz⁴⁸
Response/participation rate	<60%	3 (15.8%)	Flores et al.,³⁴ Groot et al.,³⁶ Oudin et al.⁴⁵
	≥60%	4 (21.1%)	Akpinar-Elci et al.,³⁰ Azuma et al.,³¹ Butler et al.,³² Casas et al.³⁵
	Not reported	12 (63.2%)	Chen et al.,³³ Huebner et al.,³⁷ Kang et al.,³⁸ Kilburn,^39,40 Midouhas et al.,⁴¹ Mueller and Flouri,⁴² Oloye and Flouri,⁴³ Oluyomi et al.,⁴⁴ Paterson et al.,⁴⁶ Shenassa et al.,⁴⁷ Wen and Balluz⁴⁸
Data source	Primary data collection	5 (26.3%)	Azuma et al.,³¹ Flores et al.,³⁴ Kilburn,^39,40 Oudin et al.⁴⁵
	Longitudinal cohort study secondary datasets	7 (36.8%)	Butler et al.,³² Casas et al.,³⁵ Groot et al.,³⁶ Midouhas et al.,⁴¹ Mueller and Flouri,⁴² Oloye and Flouri,⁴³ Paterson et al.⁴⁶
	Cross-sectional secondary datasets	6 (31.6%)	Akpinar-Elci et al.,³⁰ Chen et al.,³³ Huebner et al.,³⁷ Oluyomi et al.,⁴⁴ Shenassa et al.,⁴⁷ Wen and Balluz⁴⁸
	Preintervention period of an intervention study	1 (5.3%)	Kang et al.³⁸

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Table 2 Summary of individual study characteristics for 19 studies of the association between dampness and/or mold exposure and mental health, including definition and method of measurement of exposure and outcome.

Study ID	Population	Region	Flooding	Dampness/mold definition	Dampness/mold assessment	Mental health indicator	Mental health indicator assessment
Akpinar-Elci 2018³⁰	Adults	South America	Yes	Visible mold; mold smell	Self-report (validated tool)	Depressive symptoms	Self-report (validated tool)
Azuma 2014³¹	Adults	Asia	Yes	Indoor dampness	Self-report	Stress; anxiety	Self-report
Butler 2003³²	Parents	Oceania	No	Dampness/mold	Self-report	Postnatal depression	Self-report (validated tool)
Chen 2003³³	Adults	Asia	No	Visible mold	Self-report (validated tool)	Mental health	Self-report (validated tool)
Flores 2020³⁴	Adults	North America	Yes	Square feet of visible mold	Self-report	Posttraumatic stress	Self-report (validated tool)
GINIplusLISAplusStudyGrp 2013³⁵	Children	Europe	No	Visible mold at ages 0, 1, 4, 6, and 10 years	Self-report	Emotional symptoms at age 10	Self-report (validated tool)
Groot 2022³⁶	Parents	Europe	No	Visible or odorous mold	Self-report	Parental affective disorders	Self-report; data linkage
Huebner 2022³⁷	Adults	Europe	No	Dampness	Self-report	Happiness in the past 24 hours; anxiety in the past 24 hours	Self-report
Kang 2022³⁸	Adults	North America	No	Dampness/mold	Self-report	Stress; mental health	Self-report (validated tool)
Kilburn 2003⁴⁰	Adults	North America	No	Mold	Self-report; indoor air sampling (self-reported exposed group only)	Depression	Self-report (validated tool)
Kilburn 2009³⁹	Adults	North America	No	Mold	Self-report; surface sampling (self-reported exposed group only)	Depression	Self-report (validated tool)
Midouhas 2019⁴¹	Children	Europe	No	Dampness or condensation in the first wave	Self-report	Emotional symptoms at wave 2	Self-report (validated tool)
Mueller 2020⁴²	Children	Europe	No	Dampness or condensation at waves 2, 3, and 4	Self-report	Emotional dysregulation at waves 2, 3, and 4	Self-report (validated tool)
Oloye 2021⁴³	Children	Europe	No	Dampness at waves 2, 3, and 4	Self-report	Emotional dysregulation at waves 2, 3, and 4	Self-report (validated tool)
Oluyomi 2021⁴⁴	Adults	North America	Yes	Mold or musty odor	Self-report	Stress	Self-report
Oudin 2016⁴⁵	Children	Europe	No	Mold smell or visible mold	Self-report	Stress	Self-report
Paterson 2018⁴⁶	Parents	Oceania	No	Dampness	Self-report	Maternal psychological distress	Self-report (validated tool)
Shenassa 2007⁴⁷	Adults	Europe	No	Dampness and mold	Self-report; independent home assessment	Depression	Self-report (validated tool)
Wen 2011⁴⁸	Adults	North America	No	Visible mold on an area greater than the size of a dollar bill	Self-report	Mentally unhealthy days in the past 30 days	Self-report

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Dampness and Mold Assessment

Among the 19 eligible studies, 15 papers (𝑛=15, 79%) assessed mold exposure using self-reported measures only.^{30–38,41–44,46,48} Of these self-reported measures, two were validated questionnaires.^30,33 Three papers quantified the level of mold exposure in the self-report questions: one asked how many square feet of the home were covered by mold,³⁴ one quantified the level of exposure by computing a dampness and mold index,⁴⁷ while the other asked whether the amount of mold in the participant’s home exceed the size of a US one dollar bill.⁴⁸ The remaining 10 papers that used self-report exposure measures used unvalidated questionnaires, consisting of a question asking whether the participant had observed any damp or mold in their home. Of four papers that did not utilize exclusively self-reported exposure measurement, three combined self-report and independent assessment of dampness or mold^39,40,47 and the final paper utilized independent assessment only.⁴⁵ However, in the case of two papers that combined independent assessment and self-report, independent assessment was only completed for the participants who self-reported as exposed.^39,40

Distribution of Exposure in Included Studies

Figure 1 shows the geographical distribution of the countries studied in the included papers. Most studies (𝑛=17, 89%), except the two studies with participants located in more arid states of the US (California and Arizona),^39,40 were conducted in geographical regions with temperate to humid climates,^{30–38,41–48} suggesting that these climates provide an environment that is more conducive to mold growth in buildings.

Figure 1. Geographical location of included studies, marked by climate. Climates of locations of included studies are temperate/mesothermal (characterized by monthly mean air temperatures above 10°C/50°F for 4 to 7 months of the year and average temperature above 0°C/32°F in the coldest month), arid/semi-arid (characterized by low annual precipitation), tropical (characterized by mean air temperatures over 18°C/64.4°F in the coldest month and a 10- to 12-month-long wet season), and continental/microthermal (characterized by monthly mean air temperatures above 10°C/50°F for 4 to 7 months of the year and average temperature below 0°C/32°F in the coldest month).⁴⁹ Data in this Figure can be found in Table 2. Map created with mapchart.net.Open in viewer

Four studies discussed exposure to dampness or mold at least partially in relation to flooding.^30,31,34,44 In one study, indoor dampness and visible mold growth was significantly higher in homes with water damage compared with homes that had no water damage in areas of Japan that had experienced severe flooding between 2004 and 2010.³¹ Studies conducted after Hurricane Harvey found that within 45 d after the flooding event, 82% of participants’ homes had signs of mold, and 12 to 14 months after, 66.7% of participants’ homes had signs of mold, with the average area of homes covered by mold between zero and 10 square feet.^34,44 Additionally, one study found that having experienced water damage or flooding was positively correlated with mold and moisture compared with not having experienced water damage or flooding.³⁶ Only one study focused on previously flooded areas had comparatively low prevalence of visible mold with 10.7% reporting visible mold.³⁰

Exposure status varied according to housing characteristics. In two studies, a larger proportion of renters were exposed to mold compared to owner-occupiers.^32,36 Similarly, in one study, those with financial difficulties with housing costs were more often exposed compared to those who were able to afford housing costs.³² Other factors that were observed by one study to be common in those exposed to mold were high housing density, younger building age, poorer ventilation (particularly low use of exhaust fans), use of a fireplace, and presence of a gas stove.³⁶

Three studies also identified environmental factors that were more common in homes with dampness and/or mold. These included lack of greenspace,⁴² pollution,^41,42 secondhand smoke,^35,41 and pet ownership.^35,41

Mental Health Assessment

In contrast to exposure measurement methods, validated screening tools [e.g., Strengths and Difficulties Questionnaire, SF-12 Questionnaire Mental Component Summary (where a higher score indicates better mental health), Edinburgh Postnatal Depression Scale] were used in most papers (𝑛=13, 68%) to evaluate mental health.^{30,32–35,38–43,46,47} Five studies used nonvalidated questions to assess mental health impact.^{31,37,44,45,48} One study linked survey responses to patient registers to assess diagnosis of affective disorders.³⁶

Mental Health Effects in Adults

Table 3 collates all results for the seven studies conducted with adults in a normal life context.^{33,37–40,47,48}

Table 3 Summary of results reported by papers analyzing the residential dampness and/or mold exposure and mental health association in adults. Studies (𝑛=7) were included if they analyzed the dampness/mold–mental health association in adults aged 18+ years in a normal life context (i.e., not in the context of flooding or other natural disasters).

Study ID	Exposure	Outcome	Adjustments	Results	Direction of association
Chen 2023	Visible mold	Mental component summary score	—	Sometimes MD=1.48 (95% CI: 0.672, 2.29); Rarely MD=3.66 (95% CI: 2.86, 4.46); Not at all MD=6.74 (95% CI: 5.93, 7.57); 𝑝-value for trend <0.001	Positive
Chen 2023	Visible mold	Mental component summary score	Age, sex	Sometimes MD=1.5 (95% CI: 0.67, 2.32); Rarely MD=3.72 (95% CI: 2.91, 4.53); Not at all MD=6.82 (95% CI: 5.99, 7.65); 𝑝-value for trend <0.001	Positive
Chen 2023	Visible mold	Mental component summary score	Sociodemographic factors	Sometimes MD=1.51 (95% CI: 0.61, 2.4); Rarely MD=3.77 (95% CI: 2.89, 4.66); Not at all MD=6.76 (95% CI: 5.85, 7.67); 𝑝-value for trend <0.001	Positive
Huebner 2022	Damp all year	Anxiety	Sociodemographic factors, housing factors, area factors	OR=1.25 (95% CI: 1.06, 1.47; 𝑝=0.008)	Positive
Huebner 2022	Damp in winter	Anxiety	Sociodemographic factors, housing factors, area factors	OR=1.09 (95% CI: 0.92, 1.3; 𝑝=0.316)	Unclear/crosses the null
Huebner 2022	Damp (other)	Anxiety	Sociodemographic factors, housing factors, area factors	OR=0.91 (95% CI: 0.59, 1.36; 𝑝=0.655)	Unclear/crosses the null
Huebner 2022	Damp all year	Happiness	Sociodemographic factors, housing factors, area factors	OR=0.85 (95% CI: 0.74, 0.98; 𝑝=0.024)	Negative
Huebner 2022	Damp in winter	Happiness	Sociodemographic factors, housing factors, area factors	OR=0.76 (95% CI: 0.65, 0.88; 𝑝<0.001)	Negative
Huebner 2022	Damp (other)	Happiness	Sociodemographic factors, housing factors, area factors	OR=0.94 (95% CI: 0.67, 1.33; 𝑝=0.718)	Unclear/crosses the null
Kang 2022	Dampness/mold	Mental component summary score	Sociodemographic factors, clustering effects	OR=1.41 (95% CI: 0.28, 7.17; 𝑝≥0.05)	Unclear/crosses the null
Kang 2022	Dampness/mold	Stress	Sociodemographic factors, clustering effects	OR=0.57 (95% CI: 0.09, 3.74)	Unclear/crosses the null
Kilburn 2003	Mold	Profile of mood states score	Sociodemographic factors	MD=43 (𝑝<0.0001)	Positive
Kilburn 2009	Mold	Profile of mood states score	Sociodemographic factors	MD=47.1 (𝑝<0.0001)	Positive
Shenassa 2007	Dampness and mold	Depression	Sociodemographic factors, housing factors	Minimal OR=1.39 (95% CI: 1.02, 1.89); Moderate OR=1.44 (95% CI: 1.08, 1.92); Extensive OR=1.34 (95% CI: 0.97, 1.85); 𝑝-value for trend=0.032	Positive
Shenassa 2007	Dampness and mold	Depression	Sociodemographic factors, housing factors, perception of control	Minimal OR=1.34 (95% CI: 0.98, 1.82); Moderate OR=1.4 (95% CI: 1.05, 1.87); Extensive OR=1.24 (95% CI: 0.9, 1.72); 𝑝-value for trend=0.069	Positive
Shenassa 2007	Dampness and mold	Depression	Sociodemographic factors, housing factors, mold-related physical health conditions	Minimal OR=1.32 (95% CI: 0.98, 1.79); Moderate OR=1.37 (95% CI: 1.02, 1.83); Extensive OR=1.15 (95% CI: 0.83, 1.61); 𝑝-value for trend=0.104	Unclear/crosses the null
Shenassa 2007	Dampness and mold	Depression	Sociodemographic factors, housing factors, perception of control, mold-related physical health conditions	Minimal OR=1.28 (95% CI: 0.94, 1.73); Moderate OR=1.34 (95% CI: 1.01. 1.79); Extensive OR=1.09 (95% CI: 0.78, 1.52); 𝑝-value for trend=0.215	Unclear/crosses the null
Wen 2011	Mold	14 or more mentally unhealthy days per month	—	OR=2.22 (95% CI: 1.65, 2.98)	Positive
Wen 2011	Mold	14 or more mentally unhealthy days per month	Sociodemographic factors, health factors	1.77 (95% CI: 1.27, 2.47; 𝑝<0.01)	Positive

Note: —, no data; CI, confidence interval; MD, mean difference; OR, odds ratio.

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Evidence that adults exposed to dampness or mold have poorer mental health compared to adults who did not have reported exposure to dampness or mold was found in six of seven studies.^{33,37–40,47,48} Findings that did not reach significance were in the direction of a positive outcome nonetheless.³⁸

In two studies, higher depression, tension, anger, fatigue, and confusion scores and lower vigor scores were reported by the mold-exposed participants, compared with unexposed participants.^39,40 These papers hypothesized that, in combination with findings of neuropsychological and neurophysiological impairments, the observed scores were signs of impaired brain function due to potentially neurotoxic effects of mycotoxin exposure.^39,40

Several studies speculated on the pathways through which exposure to mold in the home impacts mental health. The psychosocial effects of living in poor quality housing were commonly cited to explain observed associations. Two papers suggested that the adverse mental health effects of damp and moldy housing may be a product of concerns about the health effects of damp conditions, the need for housing maintenance to be performed, the financial burden of problems with one’s home, dissatisfaction with one’s dwellings, and the social isolation caused by a reluctance to host family and friends in a damp and moldy home.^32,46 Similarly, one analysis found that perceived control over housing conditions modified the relationship between residential mold exposure and depressive symptoms.⁴⁷ The physical discomfort associated with residing in a mold-affected home may explain the association, as may experiencing physical health problems attributed to dampness/mold exposure.^34,47

Several studies proposed that the association is more direct, through physiological pathways. Two studies suggest that the cognitive effects of mold exposure may be an explanation for the associations identified in their studies.^34,47 An additional hypothesis was that exposure to mold may lead to hypoactivation of the prefrontal cortex, which is responsible for regulating thoughts, actions, and emotions.⁴⁷ Finally, one paper speculated that exposure to dampness or mold may alter serotonin and glutamate transmission or the activity of the HPA axis.⁴¹

Mental Health Effects after Flooding Events

Table 4 collates results for the four studies conducted in the context of flooding events.^30,31,34,44

Table 4 Summary of results reported by papers analyzing the residential dampness and/or mold exposure and mental health association in the aftermath of natural disasters such as flooding. Studies (𝑛=4) were included if they analyzed the dampness/mold–mental health association in adults aged 18+ years in the context of flooding or other natural disasters.

Study ID	Exposure	Outcome	Adjustments	Results	Direction of association
Akpinar-Elci 2018	Visible mold	Feeling downhearted and depressed	Sociodemographic factors	OR=1.3 (95% CI: 0.6, 2.8; 𝑝≥0.05)	Unclear/crosses the null
Akpinar-Elci 2018	Visible mold	Feeling downhearted and depressed	Sociodemographic factors	OR=1.5 (95% CI: 0.6, 3.3; 𝑝≥0.05)	Unclear/crosses the null
Azuma 2014	Indoor dampness	Anxiety	Sociodemographic factors	Moderate dry OR=0.05 (95% CI: 0.001, 3.16; 𝑝≥0.05); Medium OR=0.08 (95% CI: 0.002, 3.67; 𝑝≥0.05); Moderate damp OR=0.34 (95% CI: 0.008, 13.3; 𝑝≥0.05); Very damp OR=0.61 (95% CI: 0.02, 23.3; 𝑝≥0.05); 𝑝-value for trend=0.014	Unclear/crosses the null
Azuma 2014	Indoor dampness	Stress	Sociodemographic factors	Moderate dry OR=0.11 (95% CI: 0.002, 5.8; 𝑝≥0.05); Medium OR=0.56 (95% CI: 0.02, 15.3; 𝑝≥0.05); Moderate damp OR=1.84 (95% CI: 0.07, 48.1; 𝑝≥0.05); Very damp OR=2.41 (95% CI: 0.09, 61.6; 𝑝≥0.05); 𝑝-value for trend=0.013	Unclear/crosses the null
Flores 2020	Square footage of mold	Posttraumatic stress	Sociodemographic factors, natural disaster experience factors	OR=1.55 (95% CI: 1.19, 2.03; 𝑝<0.001)	Positive
Oluyomi 2021	Mold in the home	Stress	Sociodemographic factors	T1 MD=1.99 (𝑝<0.001); T2 MD=2.3 (𝑝<0.001)	Positive

Note: CI, confidence interval; MD, mean difference; OR, odds ratio.

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Evidence for a significant effect of mold exposure on acute and PTS responses after a flooding event was found by two studies.^34,44 One of these studies observed a dose–response relationship between square footage of mold and increased stress (a 1.55-fold increase in the odds of PTS with a scale-unit increase in the square footage of mold).^34,44 Findings in two studies that did not reach significance were nonetheless in the direction of a positive association, indicating that exposure to dampness or mold after experiencing flooding can increase the risk of stress, anxiety, and indicators of depression and may persist for months or years after the flooding event.^30,31

Mental Health Effects in Parents

Table 5 collates results for the three studies conducted specifically on parents.^32,36,46

Table 5 Summary of results reported by papers analyzing the residential dampness and/or mold exposure and mental health association in parents. Studies (𝑛=3) were included if they analyzed the dampness/mold–mental health association in parents in a normal life context (i.e., not in the context of flooding or other natural disasters).

Study ID	Exposure	Outcome	Adjustments	Results	Direction of association
Butler 2003³²	Dampness and mold	Postnatal depression	Sociodemographic factors	OR=1.4 (95% CI: 1.02, 1.91; 𝑝<0.05)	Positive
Groot 2022³⁶	Parental affective disorders	Mold in child’s bedroom	—	𝑝<0.001	Positive
Groot 2022³⁶	Parental affective disorders	Mold in other rooms	—	𝑝<0.001	Positive
Paterson 2018⁴⁶	Damp	Maternal psychological distress	—	OR=1.62 (95% CI: 1.08, 2.43; 𝑝<0.05)	Positive
Paterson 2018⁴⁶	Damp	Maternal psychological distress	Sociodemographic factors, housing factors, mental health factors	OR=1.09 (95% CI: 0.65, 1.83; 𝑝≥0.05)	Unclear/crosses the null

Note: —, no data; CI, confidence interval; MD, mean difference; OR, odds ratio.

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Parents are a key population of interest in understanding the mental health effects of residential mold exposure. One study found that the odds of postnatal depression is 82% higher for mothers living in a mold-affected home compared with mothers living in a home that was not affected by mold.³² Similarly, one study found that parents have higher risk of psychological distress when exposed to dampness in their home, though the association is nonsignificant after adjustment for ethnicity, marital status, postnatal depression, education, unemployment, housing that is too small, housing that is hard to get to from the street, housing in poor condition, cold housing, presence of pests in the home, housing that is too expensive, and presence of any housing problem.⁴⁶ In this study, the proportion of mothers with psychological distress was higher in exposed compared with unexposed mothers (26% vs. 18%).⁴⁶ Explanatory theories discussed in the papers include concern about the health effects, social isolation, the financial burden of remediating the home and lack of satisfaction with the home.^32,46 However, the association may be bidirectional; as in one paper, parental affective disorders were associated with higher risk of mold, moisture, and water damage, possibly due to the modified behaviors of people with mental health conditions—visible mold was present in 1% of children’s bedrooms and 5.4% of other rooms where the parents had diagnosed affective disorders, compared with 0.7% and 3.5%, respectively, where the parents had no affective disorders.³⁶

Mental Health Effects in Children

Table 6 collates the results for the five studies conducted with children as the population of interest.^{35,41–43,45}

Table 6 Summary of results reported by papers analyzing the residential dampness and/or mold exposure and mental health association in children. Studies (𝑛=5) were included if they analyzed the dampness/mold–mental health association in children aged under 18 years in a normal life context (i.e., not in the context of flooding or other natural disasters).

Study ID	Exposure	Outcome	Adjustments	Results	Direction of association
GINIplusLISAplusStudyGrp 2013³⁵	Visible mold	Emotional symptoms	Cohort, region	OR=1.38 (95% CI: 1.18, 1.61; 𝑝<0.05)	Positive
GINIplusLISAplusStudyGrp 2013³⁵	Visible mold	Emotional symptoms	Cohort, region, sociodemographic factors, environmental factors	OR=1.39 (95% CI: 1.16, 1.66; 𝑝<0.05)	Positive
GINIplusLISAplusStudyGrp 2013³⁵	Visible mold	Emotional symptoms	Cohort, region, sociodemographic factors, environmental factors, pet ownership	OR=1.4 (95% CI: 1.16, 1.69; 𝑝<0.05)	Positive
Midouhas 2019⁴¹	Damp or condensation	Emotional symptoms	Sociodemographic factors, environmental factors, housing factors, child factors, MCS strata	MD=0.09 (95% CI: 0.002, 0.17; 𝑝<0.05)	Positive
Mueller 2020⁴²	Damp or condensation	Emotional dysregulation	Linear age term, quadratic age term, sociodemographic factors, environmental factors, housing factors, child factors	MD=0.021 (95% CI: 0.012, 0.03; 𝑝<0.01)	Positive
Oloye 2021⁴³	Damp	Emotional dysregulation	—	MD=0.025 (95% CI: 0.0016, 0.034; 𝑝<0.01)	Positive
Oloye 2021⁴³	Damp	Emotional dysregulation	Linear and quadratic age terms, housing factors, sociodemographic factors, area factors	MD=0.016 (95% CI: 0.007, 0.026; 𝑝<0.01)	Positive
Oudin 2016⁴⁵	Mold	Stress	—	OR=1.05 (95% CI: 0.22, 5.07)	Unclear/crosses the null

Note: —, no data; CI, confidence interval; MD, mean difference; OR, odds ratio.

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Significant associations were observed between exposure to damp housing and emotional dysregulation and symptoms in children under 10 years of age, with effect measures ranging from 0.09- to 0.021-point increases in the emotional dysregulation/emotional symptoms and significant correlations between exposure and outcome to 40% increases in the odds of emotional dysregulation.^35,41–43 Similarly to other effects, the only nonsignificant finding skewed toward a positive association between exposure to mold and stress [unadjusted odds ratio (OR)=1.05; 95% confidence interval (CI): 0.22, 5.07].⁴⁵ Proposed pathways included neuroinflammation and neurotoxicity, changes in neurotransmitter transmission, and changes in the hypothalamic–pituitary–adrenal (HPA) axis.^35,41–43

Discussion

Poor housing conditions have been consistently associated with poor mood and mental health in adults.^12,15–17 In this review, a common thread between included papers was the finding that residential dampness or mold exposure had a harmful effect on participants’ mental health. In adults, statistically significant associations were reported by papers examining depressive symptoms^32,39,40,47 and self-reported mental health.^33,48 In children, statistically significant associations were reported by studies examining emotional dysregulation^42,43 and emotional symptoms.^35,41

Preliminary research hypothesizes that exposure to biological, chemical, and physical hazards due to poor housing conditions may affect physiological and biochemical processes in the brain.⁵⁰ Indeed, several of the included studies hypothesized that the mental health effects were due to the biochemical effects of mold inhalation.^{35,39–43,47} A study of mold inhalation in mice found that exposure impaired memory and induced anxiety-like behavior through innate immune activation.⁵¹ However, more research is needed to ascertain whether these processes are observed in humans. Future studies would benefit from objective measurement of biomarkers or use of magnetic resonance imaging (MRI) in exposed vs. unexposed humans and their associations with mental health outcomes to explore these hypothesized mechanisms further.

There remain some challenges in the generalizability of our findings despite a relatively diverse dataset. Data are lacking in several countries, geographic regions, and populations. European countries and some states of the US were overrepresented in the set of papers under study. No papers included African countries, and South America and Asia were only represented by one and two papers, respectively. Additionally, while there is evidence that there is geographic variation in predominant species of mold, existent research does not explore whether there is a differential impact of species of mold on mental health. Much of the available literature on dampness or mold exposure in adults comes from populations affected by household flooding.^30,31,34,44 This limits our interpretation of the available evidence since data on flood-affected populations cannot be generalizable to normal-life contexts. Given the diverse climatic and housing conditions globally, our knowledge of how exposure to mold or dampness impacts mental health has limited generalizability beyond the study’s individual context.

While a study quality analysis was not undertaken, the included papers were deemed to be of generally low quality. For example, most studies were cross-sectional analyses of nonrepresentative samples.^{30–34,37,38,44–48} The representativeness of many of the included papers was compromised due to low response rates and selection bias, especially in the two case-control studies, where cases were self-selected into the studies.^39,40 Most studies used self-reported measures of both exposure and outcome, many of which were not validated tools. It was also difficult to reliably distinguish between poor-quality data collection and analysis vs. inadequate reporting of methods and results. In future studies, we suggest that established reporting guidelines for observational studies are used so that study findings can adequately contribute to the body of evidence.

Preexisting mental health conditions or history of mental illness were not factored into any of the analyses, which could confound the association or indicate the presence of selection effects of people with poor mental health into moldy homes. As a consequence, we cannot rule out the possibility of reverse causation, whereby mental health problems affect residents’ ability to care for their home, therefore leading to mold growth. Indeed, one study in our sample found that the poor parental mental health was associated with the presence of damp in the home.³⁶ Given that occupant behaviors influence mold growth,⁵² it is plausible that the symptoms of mental health, including fatigue, cognitive symptoms, and low motivation,⁵³ may affect the ability to engage in activities that prevent mold, such as regular cleaning and ventilation of the home. In future studies, it will be important to establish temporality, i.e., whether mold was present before onset of mental health problems, whether mental health problems existed prior to mold appearing, or whether both mold and mental health problems appeared concurrently.

It is important to note the challenges posed by conducting mold studies. It is difficult to objectively measure and quantify mold exposure, as shown by most of the included studies, which used simple binary variables with a broad definition of mold or used dampness as a proxy for mold exposure. Little is known how well self-reported exposure to mold correlates with actual exposure, and the likelihood of reporting bias may be high, both in terms of overreporting and underreporting presence and/or severity of mold.⁵⁴ Some of the included studies attempted to better quantify levels of exposure by using more specific definitions (e.g., mold on an area greater than a US $1 bill),⁴⁸ creating an index to determine level of mold exposure,⁴⁷ or conducting fungal sampling.^39,40 However, there are no standardized methods for evaluating a home for indoor fungal exposure. Currently, presence of visible mold, mold smell, or measures of moisture are the most accurate indicators of a home having a problem with mold growth.⁵⁵ Indeed, a review of metrics for assessing residential dampness and mold found that visual mold and mold smell were useful indicators of not just the presence of dampness and mold but also the magnitude of risk for health effects in epidemiological studies, and awareness of these metrics may improve public health while being more objective.⁵⁶ However, the authors emphasize that visual and smell-based metrics for mold exposure are proxy variables for the causal agents and are imprecise, unclear, and inconsistent.⁵⁶ Quantitative assessment tools for mold exposure remain in their infancy. Many existing methods of sampling and quantifying mold exposure are considered inaccurate and lacking validity, unless many samples are taken per home.¹ Polymerase chain reaction (PCR) testing for microbial constituents have detected certain fungi, such as Aspergillus and Cladosporium, due to their high sensitivity and specificity.¹ However, due to the experimental nature and limited commercial availability of PCR testing, it is not widely used.¹ The Environmental Relative Moldiness Index is an example of exposure assessment that uses PCR testing of dust sampling.⁵⁷ The cross-sectional nature of the measurements mean that the sampling results may not accurately reflect the actual concentration of fungi and variation in exposure over time, and these cross-sectional measurements may be impacted by outdoor air quality and resident activities at the time of measurement.⁵⁷ These issues with quantifying mold exposure also make it difficult to assess the sensitivity of study results to choice of exposure (such as dampness vs. mold vs. extent of mold), as no standardized exposure measurements or definitions are available across studies.

This review has some limitations that must be considered. First, since our search was restricted to published, peer-reviewed studies in English, we cannot dismiss the possibility of publication bias due to noninclusion of studies published in languages other than English, unpublished studies, nonpeer reviewed studies, or gray literature. Few of the included papers generated null results, and no results were contrary to the findings of previous research, which may indicate the presence of publication bias. Given that statistical significance and effect size are predictors of publication, both on the side of the author and the publisher,⁵⁸ it is possible that studies with nonsignificant or negative results may not have been published. With regards to small study effects, smaller studies with sample sizes below 1,000 were equally likely to report statistically nonsignificant effects or significant effects; four of the seven studies with smaller sample sizes reported nonsignificant effects,^30,31,38,46 and the other three reported statistically significant effects,^34,39,40 so while publication bias from smaller studies may be present, the likelihood is minimal. Second, due to the considerable heterogeneity in both exposure and outcomes and their measurement methods, a systematic review and meta-analysis, which would have provided more rigorous and concrete findings, was not suitable.

Future studies would benefit from investigations of the association between mold exposure and mental health that clearly conceptualize the pathways hypothesized to influence the association, utilize large sample sizes with adequate statistical power, use independent measures of exposure (such as home inspection or mold sampling) and outcome (such as validated screening tests/records of mental health diagnoses), and report both significant and nonsignificant results.

In addition, we note that significant gaps remain in our understanding of the mental health effects of dampness or mold exposure. A greater focus on the pathways between residential dampness/mold exposure and mental health could provide a more detailed understanding of the issue. While included papers hypothesized that there are psychosocial and physiological mechanisms by which mold exposure may influence mental health, these mechanisms remain largely unstudied. It is also recommended that further research be undertaken on identification of at-risk subgroups who may be more susceptible to poor mental health when living in damp- or mold-affected housing and effects of residential dampness and mold exposure over time, particularly in adults.

Acknowledgments

The authors’ contributions to this work were as follows. M.R.G., project administration, conceptualization, methodology, data curation, formal analysis, investigation, data curation, writing – original draft, writing – review and editing, and visualization. A.M., data curation, investigation, formal analysis, and writing – review and editing. A.L., project administration, conceptualization, methodology, writing – review and editing, and supervision. R.B., project administration, conceptualization, methodology, writing – review and editing, and supervision.

This research was supported by an Australian Government Research Training Program Scholarship awarded to M.R.G. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the University of Melbourne.

Article Notes

The authors declare they have no actual or potential competing financial interests.

Supplementary Material

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References

1. WHO (World Health Organisation). 2009. WHO Guidelines for Indoor Air Quality: Dampness and Mould. Heseltine E, Rosen J, eds. Geneva, Switzerland: World Health Organisation.

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No mobile information will be shared with third parties/affiliates for marketing/promotional purposes. All the above categories exclude text messaging originator opt-in data and consent; this information will not be shared with any third parties. © COPYRIGHT 2024 NTX Enviro