Cleaning products and classes associated with poor respiratory health

Cleaning products and classes associated with poor respiratory health | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Cleaning products and classes associated with poor respiratory health Xin Dai, Michael J Abramson, Garun S Hamilton, Bruce Thompson, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7558837/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 Mar, 2026 Read the published version in Environmental Science and Pollution Research → Version 1 posted 6 You are reading this latest preprint version Abstract Exposure to cleaning products may harm the lungs, mainly through inhalation. Given increased use of multiple cleaning prducts at work and home, understanding the impacts of their interplay, rather than individual exposures, is critical, but had not been investigated to date. We aim to investigate the cross-sectional association between exposure to cleaning products at home and/or in the workplace and respiratory health. We conducted a cross-sectional analysis of 318 adults from the Melbourne arm of the ECRHS III. Cleaning product exposure was assessed through questionnaires, categorizing participant exposure into seven product groups. Latent Class Analysis was used to identify exposure classes. Adjusted multivariable regression modelled associations between cleaning product classes and respiratory outcomes. We identified four classes of exposure to cleaning products: “Minimal users”, “Light users“, “Moderate users”, “Heavy users”. The most exposed “Heavy user group” characterised people using many different cleaning products on a weekly basis (especially bleach, sprays, polish, solvents, acids). This class was associated with increased risks of current asthma (OR: 3.24, 95%CI 1.19–8.77), and lower post-bronchodilator FEV 1 (z-score: -0.47) and FVC (-0.46) compared with “Minimal users”.. We found evidence of four distinct cleaning product exposure classes. Frequent use of multiple cleaning products was linked to more asthma and lower lung function, suggesting potential combined effects. These findings highlight the need for cleaning products standards, and asthma care guidelines to mitigate risks associated with cleaning products. list: Epidemiology Air pollution Pulmonary disease Asthma Lung function COPD observational studies Figures Figure 1 Figure 2 Figure 3 1. Introduction The COVID-19 pandemic has significantly heightened global awareness of hygiene practices, leading to increased use of cleaning products in homes and public spaces. These practices, aimed at eliminating viruses and bacteria, involve a broad range of cleaning products, including general sprays, acids, bleach, ammonia, degreasers and other chemicals. Evidence on the safety of cleaning products for respiratory heath is largely based on occupational exposures in adults. It has been found that exposure to chemical agents may irritate the lungs and cause inflammation, leading to adverse respiratory health among occupationally exposed workers (Dumas et al. 2019 ; Patel et al. 2024; Dang et al. 2022 ; Vizcaya et al. 2015). Current asthma and chronic obstructive pulmonary disease (COPD) management guidelines rarely mention the safety of using cleaning products in the home (Asthma 2024 ; Disease. 2024), because of the lack of evidence on relationships between commonly used cleaning products in daily life and respiratory health. Given the large, increasingly exposed population, it is important to explore the potential impact of commonly used cleaning products on respiratory health. Cleaning products contain complex ingredients, varying according to their type (sprays, liquids, foams) and use (multipurpose, kitchen surfaces, bathrooms, glass, polishing, etc). It is common for home cleaning practices to use multiple cleaning products together, potentially leading to combined effects on respiratory health. Additionally, use of multiple cleaning products may amplify these impacts by increasing overall exposure. While previous studies have primarily focused on individual ingredients or specific products, these approaches may not fully capture the risks posed the use of mixtures of products in real-world cleaning practices. Latent Class Analysis (LCA) identifies groups of individuals with similar exposure profiles, allowing for the identification of combinations of cleaning product exposures for similarly exposed individuals. Data collected from participants in the Melbourne arm of the population-based European Community Respiratory Health Survey (ECRHS) offered an opportunity to explore associations between LCA defined exposure groups to various cleaning products, both at home and work, and asthma, COPD, and lung function among adults. 2. Methods 2.1 Setting and participants The European Community Respiratory Health Survey (ECRHS) is a large, multi-centre, international research project initiated in the early 1990s to investigate the prevalence, risk factors, and long-term health outcomes of asthma (Svanes et al. 2018 ; Zock et al. 2007). The Australian center collected data from 754 participants from a random general adult population (N = 552) and a symptomatic sample (N = 202) in Melbourne, with multiple follow-ups to track changes in respiratory health over time. We used cross-sectional data from the third Melbourne follow-up (2010–2012), that recruited 550 participants with 318 completing the main questionnaire, and 277 undergoing clinical tests for lung function. Ethic approval for this study was obtained from Monash University Human Research Ethics Committee (Project number: CF11/1818–2011001012) on 27th September, 2011. Participants gave written consents to participant in the study before taking part. Clinical trial number is not applicable for this study. 2.2 Cleaning product exposure Information on exposure to cleaning products at work and home was collected through the main questionnaire for ECRHS III. Participants recorded the frequency of use for ten common types of cleaning products at home. These were bleach, ammonia, stain removers or other solvents, acids (e.g., decalcifiers, liquid scale removers, vinegar, hydrochloric acid), liquid or solid furniture polish or wax, furniture sprays, floor mopping sprays, glass cleaning sprays, and degreasing sprays such as oven cleaners. Additionally, three types of cleaning products were recorded for occupational exposure: alcohol, soaps or foams, and any other chemical product for disinfecting hands, and other chemical disinfectants e.g., glutaraldehyde, formaldehyde, chloramine-T, quaternary ammonium compounds. All cleaning products were categorized into seven groups regardless of exposure location: bleach, all sprays, occupational chemicals, all polishes, ammonia, stain removers or solvents, and acids. Participants responding “yes” to any specific cleaning products were categorized as being exposed to that product type. In addition, frequent users of cleaning products were defined as participants who self-reported using any cleaning products on a weekly basis, either 1–3 days per week or 4–7 days per week. In contrast, infrequent users were defined as participants who self-reported using cleaning products less frequently, including never or less than 1 day per week. 2.3 Asthma, COPD and Lung Function We defined current asthma by self-report of any episode of asthma or any asthma medication taken in the past 12 months. Lung function was measured with an EasyOne ultrasonic spirometer (NDD Medizintechnik AG, Zürich, Switzerland). Spirometry was repeated 15 minutes after 200 µg of salbutamol administered via a spacer. Forced expiratory volume (FEV 1 ) and Forced vital capacity (FVC) were recorded as the best of three manoeuvres, expressed as z-scores (Quanjer et al. 2012). COPD was defined as post-bronchodilator (BD) FEV 1 /FVC below the Lower Limit of Normal (LLN) (Global Initiative for Chronic Obstructive Lung Disease (Gold) 2022 ). 2.4 Other variables Occupation was recorded using a job questionnaire and coded according to the International Standard Classification of Occupations (ISCO-88) four-digit classification. Based on ISCO-88, six occupational skill levels were categorized as follows: “unemployed / student / retired / housewife,” “elementary occupation,” “all workers / clerks / machine operators,” “technicians,” “professionals,” and “legislators / senior officials and managers”. Current smoker was defined as any smoking as of one month ago at time of interview. The body mass index (BMI) was defined as the body weight (kg) divided by the square of the body height (m). Atopy was defined as an average Skin Prick Tests (SPTs) wheal diameter of 3mm or greater for 1 or more of the allergens tested. 2.5 Statistical analysis The LCA aimed to classify participants into mutually exclusively sub-groups of an unobserved latent profile, based on the similarity of their patterns of using cleaning products. Participants were assigned to the class for which they had the highest probability of membership. Details of LCA methods are given in the Supplementary material. The model fit characteristics for classes are in e- Table 1 . To test whether the exposed profiles primarily reflected occupational exposure, we conducted a Chi-Square test comparing the proportions of participants engaged in occupations with high exposure to cleaning products (e.g., professional cleaners, dry cleaners, healthcare workers, and food industry workers) across the four profiles. The associations between LCA profiles and risk of asthma/lung function were determined using multivariable regression. Potential confounders, chosen with reference to the literature and Directed Acyclic Graphs (DAGs) (e-Figure 1) were included in the final model. For asthma, we adjusted for age, sex, occupation, BMI and current smoking. For lung function, we adjusted for occupation and current smoking. We also performed a standard multivariable regression between each individual cleaning product exposure and respiratory outcomes, in order to compare the results with those found from the LCA models. A sensitivity analysis was conducted by including only the random general adult population from ECRHS I(excluding the symprtomatic sample). All analyses were performed using Stata for windows (StataCorp, Stata Statistical Software: Release 14.2, College Station, TX, USA). 3. Results The characteristics of ECRHS III participants from Melbourne are presented in Table 1 . Participants were, on average, 55 years old (Standard deviation [SD] 6.23), and 28 (8.8%) reported current smoking. Current asthma and COPD were identified in 49 (15.6%) and 35 (12.9%) participants. The majority of participants were in mid to high level occupations, with 78.5% working as clerks, machine operators, general workers, technician or professionals. 3.1 Latent class exposure profiles The best fit was the LCA model with four classes supported by the lowest adjusted Bayesian information criterion along with other fit parameters (e-table 1). There was no substantial improvement in models with more than four classes. The four classes were labelled as “Minimal users (reference)”, “light users (predominant spray)”, “Moderate users”, and “Heavy users” (Fig. 1). The prevalence and characteristics of cleaning product profiles are shown in Table 2 . The most exposed profile, "Heavy users" had a higher likelihood of using all cleaning products, especially bleach, sprays, polish, solvents, and acids, whereas the least exposed profile was more likely to represent participants who did not use cleaning products either at work or at home. Figure 1. Heatmap of cleaning product classes determined by the latent class analysis (LCA) Our LCA profiles were derived from both occupational and household exposures. The proportions of participants engaged in occupations with high exposure at work from “Minimal users” to “Heavy users”, were 15.0%, 13.5%, 12.0%, and 12.5%, respectively (Table 2 ). There was no significant differences between the profiles for the proportions of participants engaged in high-exposure occupations (P = 0.95). Our LCA classes did not incorporate the frequency of cleaning product use because they were unable to achieve convergence when both type and frequency of cleaning product use were included. To investigate further, we compared the proportions of frequent users across each profile. This analysis revealed that the proportion of frequent users was significantly higher in the "Heavy users” compared to the "Minimal users” (Table 3 ). This suggested that participants who used multiple cleaning products were also more likely to be frequent users. Additionally we conducted a sensitivity analysis including only the random participant sample (n = 239) (excluding the symptomatic sample). This did not alter the estimated associations between cleaning product profiles and respiratory outcomes (e-Table 3 ). However, the associations with lung function were attenuated, which may be due to the smaller sample size. 3.2 The association between cleaning product profiles and asthma / COPD / lung function. Belonging to the “Heavy users” profile was associated with increased odds of current asthma compared with the “Minimal users”[Odds Ratio (OR) 3.24, 95% confidence interval (CI) 1.19, 8.77] (Fig. 2 ). We found no evidence of strong associations for those belonging to the “Moderate users”(OR 1.25, 95% CI 0.46, 3.37) or the “light users” profiles (OR: 0.96, 95% CI 0.36, 2.55). We did not find an association between cleaning product profiles and COPD (Table 4 ). The findings for lung function suggested a consistent impact on both pre- and post-BD parameters. Belonging to the “Heavy users” profile was strongly associated with reduced lung function parameters, including pre-bronchodilator FEV 1 (β-coefficient for z-score: -0.57 [95%CI -0.97, -0.17]), FVC (-0.46 [-0.82, -0.11]), post-bronchodilator FEV 1 (-0.47 [-0.86, -0.07]), and FVC (-0.46 [-0.83, -0.08]), compared with the “Minimal users” profile (Fig. 3 ). Additionally, there were weak associations observed between the 'Moderate users” profile and pre- and post-BD FVC (-0.23 [-0.59, 0.02] and − 0.19 [-0.51, 0.12], respectively). We did not observe evidence for associations between these profiles and FEV 1 /FVC ratio. 3.3 Individual household exposures We observed few associations between the seven individual cleaning product exposures and asthma, COPD, or lung function (e-Table 2). Bleach was associated with increased odds of current asthma (OR 2.48 [95%CI 1.10, 5.63]), while solvents were associated with reduced pre-BD FEV 1 /FVC (β-coefficient for z-score: -0.27 [-0.53, -0.02]). Interestingly, sprays and acids showed inverse associations with respiratory outcomes, including asthma and COPD. Overall, no consistent trend emerged linking any specific cleaning product to respiratory outcomes. 4. Discussion Using comprehensive data from the Melbourne arm of ECRHS III, we found that exposure to cleaning products was associated with both current asthma and reduced lung function. There were particularly elevated risks observed among individuals who used multiple cleaning products on at least a weekly basis. To our knowledge, this is the first study to investigate respiratory health risks by integrating a comprehensive list of occupational and household cleaning products into innovative LCA-derived classes. These classes reflect real-world exposure patterns and provide meaningful implications for public health and workplace safety. Our findings support the development of detailed guidelines for using cleaning products, which may inform future asthma guidelines and risk reduction of accelerated lung function decline. Risk reduction measures related to cleaning products for risk reduction and management of asthma are poorly identified in current guidelines. Although the Global Strategy for Asthma Management and Prevention 2024 recognised indoor air pollution as an avoidable risk factor for asthma management, it only focused on the toxic gases generated from cooking and heating (Asthma 2024 ). Our results highlight the complex relationships between cleaning products and lung health, suggesting that combined use of these products may have greater effects that were not captured when each class was assessed individually. Growing evidence links cleaning products to increased asthma risk and lung function decline in adults. An analysis of ECRHS (waves I – II) of 3,503 adults from 10 countries, found that those asthma-free at baseline, who engaged in household cleaning weekly over 9 years had higher asthma risk [relative risk (RR) 1.49, 95%CI: 1.22–1.99], with a dose-response relationship for increased frequency of spray use (P < 0.05) (Zock et al. 2007). Additionally, another ECRHS study (waves II - III) of 6,235 participants from 22 centers found that women exposed to cleaning products at home or work experienced accelerated lung function decline over 20 years (Svanes et al. 2018 ). Similarly, a cross-sectional study of 37,043 French adults showed daily use of cleaning products, including irritants, “green” products, and sprays, was associated with a 2- to 3-fold increased risk of uncontrolled asthma (Pacheco Da Silva et al. 2024). However, these studies generally investigated cleaning products individually, an approach that may have failed to capture combined effects. In contrast, our study revealed that participants in the most exposed profile (“Heavy users”) had the highest respiratory health risks, exceeding the sum of individual effects derived from traditional regression analyses. Furthermore, we observed that an increasing number and frequency of cleaning product types were associated with both asthma and lung function outcomes. These findinFgs align with observations from a smaller cohort study of 103 French women, which suggested that the number of weekly household disinfectant and cleaning products used during the first trimester of pregnancy was associated with increased asthma symptom scores in mothers in the first year after delivery (OR: 1.16, 95%CI: 1.01–1.34) (Lemire et al. 2022 ). Exposure to cleaning products may cause airway irritation and chronic inflammation, which can subsequently lead to asthma symptoms and reduced lung function. Understanding the ingredients in cleaning products is crucial for precisely identifying the mechanisms underlying these risks. Many fragranced cleaning products contain volatile organic compounds (VOCs) (Steinemann et al. 2015), some of which have been linked to asthma, atopic dermatitis, and allergies (Ha et al. 2022 ; Prasasti, Haryanto, and Latif 2021; Wang et al. 2023 ). Additionally, common active chemicals in disinfectants, such as chlorine, ammonia, hypochlorite, hydrochloric acid and sodium hydroxide, have been associated with non-specific respiratory effects like reduced airway function (Clausen et al. 2020; Steinemann et al. 2015). Spray products, in particular, pose significant hazards as they facilitate inhalation and exacerbate airway inflammation (Le Moual et al. 2014). Secondary exposures are likely to be created when multiple ingredients are mixed between cleaning products or even with other household air pollutants (Clausen et al. 2020; Singer et al. 2006). Unfortunately, the lack of detailed ingredient labelling and mandatory warning on cleaning products limits consumer awareness of these potential risks, especially when these products are combined, thereby potentially amplifying their harmful effects. Our study did not detect a significant association between cleaning products and COPD. One possible explanation is that it is challenging to establish the long-term effects within a cross-sectional design, as COPD typically develops over many years. Another possible reason is the small sample size, as only 21 COPD cases were detected. However, some studies have reported links between occupational cleaning exposure and COPD. For instance, a large US cohort found that regular use of chemical disinfectants among nurses was significantly associated with COPD incidence (Dumas et al. 2019 ). Longitudinal investigation of the ECRHS cohort over 20 years found that women exposed to household and occupational cleaning products had an increased risk of airway obstruction, defined as a post-bronchodilator FEV 1 /FVC ratio below LLN (Svanes et al. 2018 ). In regression analysis for a single cleaning product, we observed a reduced risk of COPD with spray cleaning products, as well as a reduced risk of current asthma with acid cleaning products. These inconsistencies may be attributed to reverse causation and the small sample size within each cleaning product exposure group. People with asthma or COPD may avoid using these cleaning products. Given increasing evidence of adverse impacts of cleaning products, consumers should carefully consider the necessity and frequency of use. Safer practices include using respiratory protection (e.g. facemasks), ensuring effective ventilation during and after cleaning, avoiding using multiple products at the same time, and seeking out clearly labelled products. More needs to be known about individual vulnerabilities to respiratory harm e.g. infants and the elderly. We also recommend limiting the frequency of cleaning product use as much as possible. Evidence suggests that even increased use of “green” cleaning products is associated with a higher risk of uncontrolled asthma (Pacheco Da Silva et al. 2024). 5. Strengths and limitations Using the ECRHS population-based and symptomatic samples with both surveys and spirometry, makes our results applicable to the general adult population. Our data enabled consideration of multiple cleaning products together and adjustment for potential confounders. We identified cleaning product profiles using LCA, which was able to model groups of products together. The combined use of these products may have additive or synergistic effects that were not captured when we assessed these exposures individually. The LCA approach captures real-life cleaning behaviour by modelling how cleaning products are typically used by individuals in the home and at work. However a major limitation of this study was its cross-sectional design, which raises the question of reverse causation. Individuals with pre-existing asthma could be more likely to use cleaning products frequently in an effort to reduce exposure to allergens or respiratory infections. Another weakness was the reliance on self-reported exposures to cleaning products, which may not accurately reflect actual exposure. This may have introduced misclassification resulting in bias towards the null. It is difficult and expensive to measure individual concentrations of cleaning products and directly capture differences in toxicity and concentrations of each chemical, so most observational studies rely on self-report. Another challenge is identifying potential secondary chemicals when cleaning products were mixed. Although this approach may be imprecise concerning exact levels of exposure, there is evidence that survey-based answers can predict objective measurements of pollutants in household settings (Loo et al. 2010 ). 6. Conclusions Our study identified four cleaning product exposure classes based on LCA, which represented distinct exposure profiles, reflecting difference in types and frequency of use of cleaning products in real life. We found increased risk of asthma and lower lung function in adults belonging to the “Heavy users” group who had the highest risks when compared to the “Minimal users.” These findings highlight the significant short-term adverse respiratory effects associated with cleaning product use. In the post-COVID-19 era, where increased cleaning product use has become prevalent due to legitimate public health concerns, our findings demonstrate the potential unintended consequences. This serves as a critical reminder of the need for a balanced approach to hygiene practices, advocating for informed product use and the adoption of safer, less harmful cleaning practices. Declarations Consent to Participate: Participants gave written consents to participant in the study before taking part. Consent to Publish: Participants were informed that the results of this research would be published using the data collected from them. Participants were assured that no identifying or personal information would be disclosed in any publication. Competing Interests SCD and CJL are supported by Australian National Health and Medical Research Council (NHMRC) investigator grant. Other authors do not report conflict of interest. Funding sources: The Melbourne arm of ECRHS III was funded by the the Asthma Foundation of Victoria, Allen + Hanburys and National Health and Medical Research Council (NHMRC) of Australia. Author Contribution: SCD, CJL and MJA were involved with acquiring funding and/or establishing study directions and protocols. GSH, BT, GB and SK were all involved into the data collection of ECRHS III. XD led the analysis and interpretation of the data with support from SCD, CJL, MJA and CS. XD wrote the initial draft of the manuscript, which was critically revised for important content by all the authors. All authors approved the final version of the article. Acknowledgements: We thank all ECRHS participants and their families. We also thank Su-Wei Khung, Minh Le, Paulette Theodoulis, Brigitte Borg, Mahesh Dharmakumara, Christopher Stuart-Andrews and Natalie Zajakovski for their assistance with recruiting, interviewing, and testing participants. Data availability statement: Due to the sensititive nature of the questions asked in this study, study respondents were assured raw data would remain confidential and would not be shared. References Asthma, Global Initiative for (2024). '2024 GINA Main Repport. Global strategy for asthma management and prevention.'. https://ginasthma.org/wp-content/uploads/2024/05/GINA-2024-Strategy-Report-24_05_22_WMS.pdf Clausen PA, Frederiksen M, Sejbaek CS, Sorli JB, Hougaard KS, Frydendall KB, Caroe TK, Flachs EM Harald W. Meyer, Vivi Schlunssen, and Peder Wolkoff. 2020. 'Chemicals inhaled from spray cleaning and disinfection products and their respiratory effects. A comprehensive review'. 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Characteristics of study sample (N=318) Mean (SD) or N (%) Age /years 55 (6.23) Gender Male 147 (46.2) Female 171 (53.8) Current smoker 28 (8.8) Former smoker 150 (47.2) Atopy Yes 132 (52.6) No 119 (47.4) Occupations (ASCO skill level) Unemployed/student/retired/housewife 18 (6.0) Elementary occupations 13 (4.3) All workers/clerks/machine operators 98 (32.5) Technicians 22 (7.3) Professionals 117 (38.7) Legislators/senior officials/managers 34 (11.0) Current asthma 49 (15.6) COPD 35 (12.9) Table 2. Prevalence and characteristics of cleaning products identified by LCA Profile name Minimal users Light users Moderate users Heavy users Description High possibility that participants do not use cleaning products at work and at home. Higher possibilities of using bleach, spray, solvent or acids. Occupational exposure was similar to reference group. Highest possibilities of using bleach and spray, higher possibilities of using ammonia, solvent and occupational exposure. Most exposed group, highest possibilities of using bleach, spray and solvent together, higher possibilities of using polish, ammonia, acid and occupational cleaning products. N (prevalence) 80 (25.4) 104 (33.0) 75 (23.8) 56 (17.8) Male (%) 45 (56.3) 43 (41.4) 30 (40.0) 29 (51.8) Current smoker (%) 6 (7.5) 8 (7.7) 9 (12.0) 5 (8.9) Atopy (%) 40 (58.0) 39 (48.2) 33 (55.9) 19 (47.5) Participants who engaged in high exposure occupation to cleaning products (%) 12 (15.0) 14 (13.5) 9 (12.0) 7 (12.5) Table 3. The proportions of frequent users (at least once per week) across cleaning product classes Types of cleaning products Minimum users Lighter users Moderate users Heavy users P values Bleach 0% 25.0% 42.7% 46.4% <0.001 Spray 5.0% 26.9% 29.3% 41.1% <0.001 Polish 1.3% 5.8% 0% 16.1% <0.001 Occupational Chemicals 3.8% 41.4% 26.7% 53.6% <0.001 Ammonia 0% 3.9% 4.0% 12.5% <0.001 Solvent 0% 13.5% 12.0% 41.1% <0.001 Acids 0% 28.9% 0% 14.3% <0.001 Table 4. Adjusted associations* between cleaning products LCA and respiratory outcomes. Respiratory outcomes Lighter users Moderate users Heavy users Current asthma 0.96 (0.36, 2.55) 1.25 (0.46, 3.37) 3.24 (1.19, 8.77) COPD 1.04 (0.30, 3.60) 0.90 (0.23, 3.61) 2.06 (0.55, 7.73) Pre-bronchodilator (z-score) FEV 1 -0.14 (-0.45, 0.18) -0.20 (-0.54, 0.14) -0.57 (-0.97, -0.17) FVC -0.17 (-0.46, 0.11) -0.23 (-0.59, 0.02) -0.46 (-0.82, -0.11) FEV 1 /FVC 0.06 (-0.21, 0.34) 0.08 (-0.22, 0.38) -0.15 (-0.50, 0.19) Post-bronchodilator (z-score) FEV 1 -0.01 (--0.32, 0.30) -0.07 (-0.40, 0.27) -0.47 (-0.86, -0.07) FVC -0.15 (-0.45, 0.14) -0.19 (-0.51, 0.12) -0.46 (-0.83, -0.08) FEV 1 /FVC 0.24 (-0.05, 0.53) 0.19 (-0.13, 0.50) 0.04 (-0.33, 0.41) *For current asthma outcome, association was adjusted for sex, age, occupations, BMI and current smoking; for lung function outcomes, associations were adjusted for occupation and current smoking. Supplementary Files Supplementalmaterial10Apr2025.docx Cite Share Download PDF Status: Published Journal Publication published 23 Mar, 2026 Read the published version in Environmental Science and Pollution Research → Version 1 posted Editorial decision: Major Revision 30 Dec, 2025 Reviewers agreed at journal 15 Oct, 2025 Reviewers invited by journal 15 Oct, 2025 Editor invited by journal 10 Oct, 2025 Editor assigned by journal 30 Sep, 2025 First submitted to journal 24 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7558837","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":530192618,"identity":"fde3651e-9ba5-4705-8d6e-b3211a4a4a1e","order_by":0,"name":"Xin Dai","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIiWNgGAWjYDACZiDmYZCQY2BgbGBgKDgA5CYQp8UYosWAGC0MYC0MiQ1gFjFaDI7zHmB4U2ORvuF2c+uGDwZ3GPjZcwwYfrbh1iLZzJfAOOeYRO6GOwfbbs4weMYg2fPGgLEXjxZ+Zh4DZh42oJYbiW23eQwOMxjcANrCi0cLG1jLP4l0A5CWP0At9kAtjH8J2cLbJpEA1sIAskUiBySCzy88Bgfn9kkYzgRqudlj8IxH4syzgsMy53BrMTh/xvDBm2918nw30p/d+FFxR46/PXnjwzdluLWAwAFkDg+GyCgYBaNgFIwC0gEAoYNQ852nKA0AAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-0472-700X","institution":"Allergy and Lung Health Unit, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global health, the University of Melbourne, Carlton,Vic, Australia","correspondingAuthor":true,"prefix":"","firstName":"Xin","middleName":"","lastName":"Dai","suffix":""},{"id":530192619,"identity":"dc8d5c60-4210-498a-a543-4b89d216eed1","order_by":1,"name":"Michael J Abramson","email":"","orcid":"","institution":"Allergy and Lung Health Unit, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Vic, Australia; School of Public Health and Preventive Medicine, Monash University, Melbourne, Vic, Australia","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"J","lastName":"Abramson","suffix":""},{"id":530192620,"identity":"a8be61b2-9766-4b3b-8ddb-7848ca563f3d","order_by":2,"name":"Garun S Hamilton","email":"","orcid":"","institution":"Department of Lung, Sleep, Allergy and Immunology, Monash Health, Clayton, Vic, Australia; School of Clinical Sciences, Monash University, Clayton, Vic, Australia","correspondingAuthor":false,"prefix":"","firstName":"Garun","middleName":"S","lastName":"Hamilton","suffix":""},{"id":530192621,"identity":"6204b631-7999-4eb0-b6b3-406abd6790f8","order_by":3,"name":"Bruce Thompson","email":"","orcid":"","institution":"Melbourne School of Health Sciences, Faculty of Medicine, Dentistry and Health 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07:04:18","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":4722,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdjusted association between cleaning product profiles and current asthma compared to the minimal user class.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Onlinegroupimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7558837/v1/27958340f47e4328250aeed1.png"},{"id":94681628,"identity":"0ffde711-50a2-4059-ad01-46db4550e52c","added_by":"auto","created_at":"2025-10-29 14:52:39","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":26874,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdjusted association between cleaning product profiles and lung function as z-scores compared with the minimal user class.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7558837/v1/5b785118ca12aee276820fb8.png"},{"id":105755999,"identity":"470eed54-2ce8-4d43-b1c3-cc5bd1241e8a","added_by":"auto","created_at":"2026-03-30 16:34:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1329787,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7558837/v1/200899c2-048a-46a0-b9d1-5c703928dc9e.pdf"},{"id":94681639,"identity":"760066fd-90ed-423b-8eb0-3d2e8b9925d2","added_by":"auto","created_at":"2025-10-29 14:52:40","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":214925,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementalmaterial10Apr2025.docx","url":"https://assets-eu.researchsquare.com/files/rs-7558837/v1/81c565d6a3e142c8069493f7.docx"}],"financialInterests":"","formattedTitle":"Cleaning products and classes associated with poor respiratory health","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe COVID-19 pandemic has significantly heightened global awareness of hygiene practices, leading to increased use of cleaning products in homes and public spaces. These practices, aimed at eliminating viruses and bacteria, involve a broad range of cleaning products, including general sprays, acids, bleach, ammonia, degreasers and other chemicals. Evidence on the safety of cleaning products for respiratory heath is largely based on occupational exposures in adults. It has been found that exposure to chemical agents may irritate the lungs and cause inflammation, leading to adverse respiratory health among occupationally exposed workers (Dumas et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Patel et al. 2024; Dang et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Vizcaya et al. 2015). Current asthma and chronic obstructive pulmonary disease (COPD) management guidelines rarely mention the safety of using cleaning products in the home (Asthma \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Disease. 2024), because of the lack of evidence on relationships between commonly used cleaning products in daily life and respiratory health. Given the large, increasingly exposed population, it is important to explore the potential impact of commonly used cleaning products on respiratory health.\u003c/p\u003e\u003cp\u003eCleaning products contain complex ingredients, varying according to their type (sprays, liquids, foams) and use (multipurpose, kitchen surfaces, bathrooms, glass, polishing, etc). It is common for home cleaning practices to use multiple cleaning products together, potentially leading to combined effects on respiratory health. Additionally, use of multiple cleaning products may amplify these impacts by increasing overall exposure. While previous studies have primarily focused on individual ingredients or specific products, these approaches may not fully capture the risks posed the use of mixtures of products in real-world cleaning practices. Latent Class Analysis (LCA) identifies groups of individuals with similar exposure profiles, allowing for the identification of combinations of cleaning product exposures for similarly exposed individuals.\u003c/p\u003e\u003cp\u003eData collected from participants in the Melbourne arm of the population-based European Community Respiratory Health Survey (ECRHS) offered an opportunity to explore associations between LCA defined exposure groups to various cleaning products, both at home and work, and asthma, COPD, and lung function among adults.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Setting and participants\u003c/h2\u003e\u003cp\u003eThe European Community Respiratory Health Survey (ECRHS) is a large, multi-centre, international research project initiated in the early 1990s to investigate the prevalence, risk factors, and long-term health outcomes of asthma (Svanes et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Zock et al. 2007). The Australian center collected data from 754 participants from a random general adult population (N\u0026thinsp;=\u0026thinsp;552) and a symptomatic sample (N\u0026thinsp;=\u0026thinsp;202) in Melbourne, with multiple follow-ups to track changes in respiratory health over time. We used cross-sectional data from the third Melbourne follow-up (2010\u0026ndash;2012), that recruited 550 participants with 318 completing the main questionnaire, and 277 undergoing clinical tests for lung function. Ethic approval for this study was obtained from Monash University Human Research Ethics Committee (Project number: CF11/1818\u0026ndash;2011001012) on 27th September, 2011. Participants gave written consents to participant in the study before taking part. Clinical trial number is not applicable for this study.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Cleaning product exposure\u003c/h2\u003e\u003cp\u003eInformation on exposure to cleaning products at work and home was collected through the main questionnaire for ECRHS III. Participants recorded the frequency of use for ten common types of cleaning products at home. These were bleach, ammonia, stain removers or other solvents, acids (e.g., decalcifiers, liquid scale removers, vinegar, hydrochloric acid), liquid or solid furniture polish or wax, furniture sprays, floor mopping sprays, glass cleaning sprays, and degreasing sprays such as oven cleaners. Additionally, three types of cleaning products were recorded for occupational exposure: alcohol, soaps or foams, and any other chemical product for disinfecting hands, and other chemical disinfectants e.g., glutaraldehyde, formaldehyde, chloramine-T, quaternary ammonium compounds.\u003c/p\u003e\u003cp\u003eAll cleaning products were categorized into seven groups regardless of exposure location: bleach, all sprays, occupational chemicals, all polishes, ammonia, stain removers or solvents, and acids. Participants responding \u0026ldquo;yes\u0026rdquo; to any specific cleaning products were categorized as being exposed to that product type. In addition, frequent users of cleaning products were defined as participants who self-reported using any cleaning products on a weekly basis, either 1\u0026ndash;3 days per week or 4\u0026ndash;7 days per week. In contrast, infrequent users were defined as participants who self-reported using cleaning products less frequently, including never or less than 1 day per week.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Asthma, COPD and Lung Function\u003c/h2\u003e\u003cp\u003eWe defined current asthma by self-report of any episode of asthma or any asthma medication taken in the past 12 months. Lung function was measured with an EasyOne ultrasonic spirometer (NDD Medizintechnik AG, Z\u0026uuml;rich, Switzerland). Spirometry was repeated 15 minutes after 200 \u0026micro;g of salbutamol administered via a spacer. Forced expiratory volume (FEV\u003csub\u003e1\u003c/sub\u003e) and Forced vital capacity (FVC) were recorded as the best of three manoeuvres, expressed as z-scores (Quanjer et al. 2012). COPD was defined as post-bronchodilator (BD) FEV\u003csub\u003e1\u003c/sub\u003e/FVC below the Lower Limit of Normal (LLN) (Global Initiative for Chronic Obstructive Lung Disease (Gold) \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Other variables\u003c/h2\u003e\u003cp\u003eOccupation was recorded using a job questionnaire and coded according to the International Standard Classification of Occupations (ISCO-88) four-digit classification. Based on ISCO-88, six occupational skill levels were categorized as follows: \u0026ldquo;unemployed / student / retired / housewife,\u0026rdquo; \u0026ldquo;elementary occupation,\u0026rdquo; \u0026ldquo;all workers / clerks / machine operators,\u0026rdquo; \u0026ldquo;technicians,\u0026rdquo; \u0026ldquo;professionals,\u0026rdquo; and \u0026ldquo;legislators / senior officials and managers\u0026rdquo;. Current smoker was defined as any smoking as of one month ago at time of interview. The body mass index (BMI) was defined as the body weight (kg) divided by the square of the body height (m). Atopy was defined as an average Skin Prick Tests (SPTs) wheal diameter of 3mm or greater for 1 or more of the allergens tested.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Statistical analysis\u003c/h2\u003e\u003cp\u003e The LCA aimed to classify participants into mutually exclusively sub-groups of an unobserved latent profile, based on the similarity of their patterns of using cleaning products. Participants were assigned to the class for which they had the highest probability of membership. Details of LCA methods are given in the Supplementary material. The model fit characteristics for classes are in e- Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. To test whether the exposed profiles primarily reflected occupational exposure, we conducted a Chi-Square test comparing the proportions of participants engaged in occupations with high exposure to cleaning products (e.g., professional cleaners, dry cleaners, healthcare workers, and food industry workers) across the four profiles.\u003c/p\u003e\u003cp\u003eThe associations between LCA profiles and risk of asthma/lung function were determined using multivariable regression. Potential confounders, chosen with reference to the literature and Directed Acyclic Graphs (DAGs) (e-Figure 1) were included in the final model. For asthma, we adjusted for age, sex, occupation, BMI and current smoking. For lung function, we adjusted for occupation and current smoking. We also performed a standard multivariable regression between each individual cleaning product exposure and respiratory outcomes, in order to compare the results with those found from the LCA models. A sensitivity analysis was conducted by including only the random general adult population from ECRHS I(excluding the symprtomatic sample). All analyses were performed using Stata for windows (StataCorp, Stata Statistical Software: Release 14.2, College Station, TX, USA).\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eThe characteristics of ECRHS III participants from Melbourne are presented in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. Participants were, on average, 55 years old (Standard deviation [SD] 6.23), and 28 (8.8%) reported current smoking. Current asthma and COPD were identified in 49 (15.6%) and 35 (12.9%) participants. The majority of participants were in mid to high level occupations, with 78.5% working as clerks, machine operators, general workers, technician or professionals.\u003c/p\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 Latent class exposure profiles\u003c/h2\u003e\n \u003cp\u003eThe best fit was the LCA model with four classes supported by the lowest adjusted Bayesian information criterion along with other fit parameters (e-table 1). There was no substantial improvement in models with more than four classes. The four classes were labelled as \u0026ldquo;Minimal users (reference)\u0026rdquo;, \u0026ldquo;light users (predominant spray)\u0026rdquo;, \u0026ldquo;Moderate users\u0026rdquo;, and \u0026ldquo;Heavy users\u0026rdquo; (Fig. 1). The prevalence and characteristics of cleaning product profiles are shown in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. The most exposed profile, \u0026quot;Heavy users\u0026quot; had a higher likelihood of using all cleaning products, especially bleach, sprays, polish, solvents, and acids, whereas the least exposed profile was more likely to represent participants who did not use cleaning products either at work or at home.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFigure\u0026nbsp;1. Heatmap of cleaning product classes determined by the latent class analysis (LCA)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eOur LCA profiles were derived from both occupational and household exposures. The proportions of participants engaged in occupations with high exposure at work from \u0026ldquo;Minimal users\u0026rdquo; to \u0026ldquo;Heavy users\u0026rdquo;, were 15.0%, 13.5%, 12.0%, and 12.5%, respectively (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). There was no significant differences between the profiles for the proportions of participants engaged in high-exposure occupations (P\u0026thinsp;=\u0026thinsp;0.95).\u003c/p\u003e\n \u003cp\u003eOur LCA classes did not incorporate the frequency of cleaning product use because they were unable to achieve convergence when both type and frequency of cleaning product use were included. To investigate further, we compared the proportions of frequent users across each profile. This analysis revealed that the proportion of frequent users was significantly higher in the \u0026quot;Heavy users\u0026rdquo; compared to the \u0026quot;Minimal users\u0026rdquo; (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). This suggested that participants who used multiple cleaning products were also more likely to be frequent users. Additionally we conducted a sensitivity analysis including only the random participant sample (n\u0026thinsp;=\u0026thinsp;239) (excluding the symptomatic sample). This did not alter the estimated associations between cleaning product profiles and respiratory outcomes (e-Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). However, the associations with lung function were attenuated, which may be due to the smaller sample size.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ch2 align=\"left\" class=\"colspec\"\u003e3.2 The association between cleaning product profiles and asthma / COPD / lung function.\u003c/h2\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003cp\u003eBelonging to the \u0026ldquo;Heavy users\u0026rdquo; profile was associated with increased odds of current asthma compared with the \u0026ldquo;Minimal users\u0026rdquo;[Odds Ratio (OR) 3.24, 95% confidence interval (CI) 1.19, 8.77] (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). We found no evidence of strong associations for those belonging to the \u0026ldquo;Moderate users\u0026rdquo;(OR 1.25, 95% CI 0.46, 3.37) or the \u0026ldquo;light users\u0026rdquo; profiles (OR: 0.96, 95% CI 0.36, 2.55). We did not find an association between cleaning product profiles and COPD (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eThe findings for lung function suggested a consistent impact on both pre- and post-BD parameters. Belonging to the \u0026ldquo;Heavy users\u0026rdquo; profile was strongly associated with reduced lung function parameters, including pre-bronchodilator FEV\u003csub\u003e1\u003c/sub\u003e (\u0026beta;-coefficient for z-score: -0.57 [95%CI -0.97, -0.17]), FVC (-0.46 [-0.82, -0.11]), post-bronchodilator FEV\u003csub\u003e1\u003c/sub\u003e (-0.47 [-0.86, -0.07]), and FVC (-0.46 [-0.83, -0.08]), compared with the \u0026ldquo;Minimal users\u0026rdquo; profile (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Additionally, there were weak associations observed between the \u0026apos;Moderate users\u0026rdquo; profile and pre- and post-BD FVC (-0.23 [-0.59, 0.02] and \u0026minus;\u0026thinsp;0.19 [-0.51, 0.12], respectively). We did not observe evidence for associations between these profiles and FEV\u003csub\u003e1\u003c/sub\u003e/FVC ratio.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 Individual household exposures\u003c/h2\u003e\n \u003cp\u003eWe observed few associations between the seven individual cleaning product exposures and asthma, COPD, or lung function (e-Table\u0026nbsp;2). Bleach was associated with increased odds of current asthma (OR 2.48 [95%CI 1.10, 5.63]), while solvents were associated with reduced pre-BD FEV\u003csub\u003e1\u003c/sub\u003e/FVC (\u0026beta;-coefficient for z-score: -0.27 [-0.53, -0.02]). Interestingly, sprays and acids showed inverse associations with respiratory outcomes, including asthma and COPD. Overall, no consistent trend emerged linking any specific cleaning product to respiratory outcomes.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eUsing comprehensive data from the Melbourne arm of ECRHS III, we found that exposure to cleaning products was associated with both current asthma and reduced lung function. There were particularly elevated risks observed among individuals who used multiple cleaning products on at least a weekly basis. To our knowledge, this is the first study to investigate respiratory health risks by integrating a comprehensive list of occupational and household cleaning products into innovative LCA-derived classes. These classes reflect real-world exposure patterns and provide meaningful implications for public health and workplace safety. Our findings support the development of detailed guidelines for using cleaning products, which may inform future asthma guidelines and risk reduction of accelerated lung function decline.\u003c/p\u003e\u003cp\u003e Risk reduction measures related to cleaning products for risk reduction and management of asthma are poorly identified in current guidelines. Although the Global Strategy for Asthma Management and Prevention 2024 recognised indoor air pollution as an avoidable risk factor for asthma management, it only focused on the toxic gases generated from cooking and heating (Asthma \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Our results highlight the complex relationships between cleaning products and lung health, suggesting that combined use of these products may have greater effects that were not captured when each class was assessed individually.\u003c/p\u003e\u003cp\u003eGrowing evidence links cleaning products to increased asthma risk and lung function decline in adults. An analysis of ECRHS (waves I \u0026ndash; II) of 3,503 adults from 10 countries, found that those asthma-free at baseline, who engaged in household cleaning weekly over 9 years had higher asthma risk [relative risk (RR) 1.49, 95%CI: 1.22\u0026ndash;1.99], with a dose-response relationship for increased frequency of spray use (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Zock et al. 2007). Additionally, another ECRHS study (waves II - III) of 6,235 participants from 22 centers found that women exposed to cleaning products at home or work experienced accelerated lung function decline over 20 years (Svanes et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Similarly, a cross-sectional study of 37,043 French adults showed daily use of cleaning products, including irritants, \u0026ldquo;green\u0026rdquo; products, and sprays, was associated with a 2- to 3-fold increased risk of uncontrolled asthma (Pacheco Da Silva et al. 2024).\u003c/p\u003e\u003cp\u003eHowever, these studies generally investigated cleaning products individually, an approach that may have failed to capture combined effects. In contrast, our study revealed that participants in the most exposed profile (\u0026ldquo;Heavy users\u0026rdquo;) had the highest respiratory health risks, exceeding the sum of individual effects derived from traditional regression analyses. Furthermore, we observed that an increasing number and frequency of cleaning product types were associated with both asthma and lung function outcomes. These findinFgs align with observations from a smaller cohort study of 103 French women, which suggested that the number of weekly household disinfectant and cleaning products used during the first trimester of pregnancy was associated with increased asthma symptom scores in mothers in the first year after delivery (OR: 1.16, 95%CI: 1.01\u0026ndash;1.34) (Lemire et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eExposure to cleaning products may cause airway irritation and chronic inflammation, which can subsequently lead to asthma symptoms and reduced lung function. Understanding the ingredients in cleaning products is crucial for precisely identifying the mechanisms underlying these risks. Many fragranced cleaning products contain volatile organic compounds (VOCs) (Steinemann et al. 2015), some of which have been linked to asthma, atopic dermatitis, and allergies (Ha et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Prasasti, Haryanto, and Latif 2021; Wang et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Additionally, common active chemicals in disinfectants, such as chlorine, ammonia, hypochlorite, hydrochloric acid and sodium hydroxide, have been associated with non-specific respiratory effects like reduced airway function (Clausen et al. 2020; Steinemann et al. 2015). Spray products, in particular, pose significant hazards as they facilitate inhalation and exacerbate airway inflammation (Le Moual et al. 2014). Secondary exposures are likely to be created when multiple ingredients are mixed between cleaning products or even with other household air pollutants (Clausen et al. 2020; Singer et al. 2006). Unfortunately, the lack of detailed ingredient labelling and mandatory warning on cleaning products limits consumer awareness of these potential risks, especially when these products are combined, thereby potentially amplifying their harmful effects.\u003c/p\u003e\u003cp\u003eOur study did not detect a significant association between cleaning products and COPD. One possible explanation is that it is challenging to establish the long-term effects within a cross-sectional design, as COPD typically develops over many years. Another possible reason is the small sample size, as only 21 COPD cases were detected. However, some studies have reported links between occupational cleaning exposure and COPD. For instance, a large US cohort found that regular use of chemical disinfectants among nurses was significantly associated with COPD incidence (Dumas et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Longitudinal investigation of the ECRHS cohort over 20 years found that women exposed to household and occupational cleaning products had an increased risk of airway obstruction, defined as a post-bronchodilator FEV\u003csub\u003e1\u003c/sub\u003e/FVC ratio below LLN (Svanes et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In regression analysis for a single cleaning product, we observed a reduced risk of COPD with spray cleaning products, as well as a reduced risk of current asthma with acid cleaning products. These inconsistencies may be attributed to reverse causation and the small sample size within each cleaning product exposure group. People with asthma or COPD may avoid using these cleaning products.\u003c/p\u003e\u003cp\u003eGiven increasing evidence of adverse impacts of cleaning products, consumers should carefully consider the necessity and frequency of use. Safer practices include using respiratory protection (e.g. facemasks), ensuring effective ventilation during and after cleaning, avoiding using multiple products at the same time, and seeking out clearly labelled products. More needs to be known about individual vulnerabilities to respiratory harm e.g. infants and the elderly. We also recommend limiting the frequency of cleaning product use as much as possible. Evidence suggests that even increased use of \u0026ldquo;green\u0026rdquo; cleaning products is associated with a higher risk of uncontrolled asthma (Pacheco Da Silva et al. 2024).\u003c/p\u003e"},{"header":"5. Strengths and limitations","content":"\u003cp\u003eUsing the ECRHS population-based and symptomatic samples with both surveys and spirometry, makes our results applicable to the general adult population. Our data enabled consideration of multiple cleaning products together and adjustment for potential confounders. We identified cleaning product profiles using LCA, which was able to model groups of products together. The combined use of these products may have additive or synergistic effects that were not captured when we assessed these exposures individually. The LCA approach captures real-life cleaning behaviour by modelling how cleaning products are typically used by individuals in the home and at work.\u003c/p\u003e\u003cp\u003eHowever a major limitation of this study was its cross-sectional design, which raises the question of reverse causation. Individuals with pre-existing asthma could be more likely to use cleaning products frequently in an effort to reduce exposure to allergens or respiratory infections. Another weakness was the reliance on self-reported exposures to cleaning products, which may not accurately reflect actual exposure. This may have introduced misclassification resulting in bias towards the null. It is difficult and expensive to measure individual concentrations of cleaning products and directly capture differences in toxicity and concentrations of each chemical, so most observational studies rely on self-report. Another challenge is identifying potential secondary chemicals when cleaning products were mixed. Although this approach may be imprecise concerning exact levels of exposure, there is evidence that survey-based answers can predict objective measurements of pollutants in household settings (Loo et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e"},{"header":"6. Conclusions","content":"\u003cp\u003eOur study identified four cleaning product exposure classes based on LCA, which represented distinct exposure profiles, reflecting difference in types and frequency of use of cleaning products in real life. We found increased risk of asthma and lower lung function in adults belonging to the \u0026ldquo;Heavy users\u0026rdquo; group who had the highest risks when compared to the \u0026ldquo;Minimal users.\u0026rdquo; These findings highlight the significant short-term adverse respiratory effects associated with cleaning product use. In the post-COVID-19 era, where increased cleaning product use has become prevalent due to legitimate public health concerns, our findings demonstrate the potential unintended consequences. This serves as a critical reminder of the need for a balanced approach to hygiene practices, advocating for informed product use and the adoption of safer, less harmful cleaning practices.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConsent to Participate:\u003c/h2\u003e\u003cp\u003eParticipants gave written consents to participant in the study before taking part.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent to Publish:\u003c/strong\u003e\u003cp\u003eParticipants were informed that the results of this research would be published using the data collected from them. Participants were assured that no identifying or personal information would be disclosed in any publication.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003cp\u003eSCD and CJL are supported by Australian National Health and Medical Research Council (NHMRC) investigator grant. Other authors do not report conflict of interest.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding sources:\u003c/h2\u003e\u003cp\u003eThe Melbourne arm of ECRHS III was funded by the the Asthma Foundation of Victoria, Allen\u0026thinsp;+\u0026thinsp;Hanburys and National Health and Medical Research Council (NHMRC) of Australia.\u003c/p\u003e\u003ch2\u003eAuthor Contribution:\u003c/h2\u003e\u003cp\u003eSCD, CJL and MJA were involved with acquiring funding and/or establishing study directions and protocols. GSH, BT, GB and SK were all involved into the data collection of ECRHS III. XD led the analysis and interpretation of the data with support from SCD, CJL, MJA and CS. XD wrote the initial draft of the manuscript, which was critically revised for important content by all the authors. All authors approved the final version of the article.\u003c/p\u003e\u003ch2\u003eAcknowledgements:\u003c/h2\u003e\u003cp\u003eWe thank all ECRHS participants and their families. We also thank Su-Wei Khung, Minh Le, Paulette Theodoulis, Brigitte Borg, Mahesh Dharmakumara, Christopher Stuart-Andrews and Natalie Zajakovski for their assistance with recruiting, interviewing, and testing participants.\u003c/p\u003e\u003ch2\u003eData availability statement:\u003c/h2\u003e\u003cp\u003eDue to the sensititive nature of the questions asked in this study, study respondents were assured raw data would remain confidential and would not be shared.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAsthma, Global Initiative for (2024). '2024 GINA Main Repport. Global strategy for asthma management and prevention.'. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ginasthma.org/wp-content/uploads/2024/05/GINA-2024-Strategy-Report-24_05_22_WMS.pdf\u003c/span\u003e\u003cspan address=\"https://ginasthma.org/wp-content/uploads/2024/05/GINA-2024-Strategy-Report-24_05_22_WMS.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eClausen PA, Frederiksen M, Sejbaek CS, Sorli JB, Hougaard KS, Frydendall KB, Caroe TK, Flachs EM Harald W. Meyer, Vivi Schlunssen, and Peder Wolkoff. 2020. 'Chemicals inhaled from spray cleaning and disinfection products and their respiratory effects. A comprehensive review'. 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Korea (South): Korean Academy of Medical Science\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLe Moual, Nicole M, Rava Val\u0026eacute;rie Siroux, R\u0026eacute;gis Matran, Rachel Nadif, Genetics Epidemiological Study on the, and Asthma Environment of. 2014. Use of household cleaning products, exhaled nitric oxide and lung function in females. In \u003cem\u003eThe European Respiratory Journal\u003c/em\u003e, 816\u0026thinsp;\u0026ndash;\u0026thinsp;18. 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In \u003cem\u003eInternational Journal of Environmental Research and Public Health\u003c/em\u003e, 3270-97. Switzerland: MDPI\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSilva PD, Varraso ERapha\u0026euml;lle, Lenzotti A-M, L\u0026eacute;opoldK, Fezeu G, Sit P, Galan S, Hercberg Mathilde Touvier, Christophe Paris, Orianne Dumas, and Nicole Le Moual. 2024. 'Household Use of Green Cleaning Products, Disinfecting Wipes, and Asthma Control Among Adults', \u003cem\u003eJournal of Allergy and Clinical Immunology: In Practice\u003c/em\u003e, 12: 919\u0026thinsp;\u0026ndash;\u0026thinsp;26.e7\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePatel J, de Porras DGR, Mitchell LE, Carson A, Whitehead LW, Han I, Pompeii L, Conway S, Zock J-P Paul K. Henneberger, Riddhi Patel, Joy De Los Reyes, and George L. Delclos. 2024. 'Cleaning Tasks and Products and Asthma Among Health Care Professionals'. Occup Environ Med, 66: 28\u0026ndash;34\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePrasasti CI, Haryanto B, Mohd Talib L (2021) Association of VOCs, PM\u0026thinsp;\u0026lt;\u0026thinsp;sub\u0026thinsp;\u0026gt;\u0026thinsp;2.5\u0026thinsp;and household environmental exposure with children\u0026rsquo;s respiratory allergies. Air Qual Atmos Health: Int J 14:1279\u0026ndash;1287\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQuanjer PH, Stanojevic S, Cole TJ, Baur X, Hall GL, Bruce H, Culver PL, Enright JL, Hankinson, Mary SM, Ip J, Zheng J, Stocks and E. R. S. Global Lung Function. 2012. 'Multi-ethnic reference values for spirometry for the 3-95-yr age range: the global lung function 2012 equations'. Eur Respir J, 40: 1324\u0026ndash;1343\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSinger BC, Beverly K, Coleman H, Destaillats AT, Hodgson MM, Lunden CJ, Weschler and William W. Nazaroff. 2006. 'Indoor secondary pollutants from cleaning product and air freshener use in the presence of ozone'. Atmos Environ, 40: 6696\u0026ndash;6710\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSteinemann AC, Ian C, MacGregor SM, Gordon LG, Gallagher AL, Davis DS, Ribeiro and Lance A. Wallace. 2015. 'Fragranced consumer products: Chemicals emitted; ingredients unlisted'. ACNEM J, 34: 10\u0026ndash;16\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSvanes O, Bertelsen RJ, Stein HL, Lygre AE, Carsin JM, Anto B, Forsberg, Jose M, Garcia-Garcia JA, Gullon JP, Zock, and Cecilie Svanes (2018). 'Cleaning at Homeat Work in Relation to Lung Function DeclineAirway Obstruction', \u003cem\u003eAm. J. Respir. Crit. Care Med.\u003c/em\u003e, 197: 1157-63\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVizcaya D, Mirabelli MC, Gimeno D, Ant\u0026oacute; J-M, Delclos GL, Rivera M, Orriols R Lourdes Arjona, Felip Burgos, and Jan-Paul Zock. 2015. 'Cleaning products and short-term respiratory effects among female cleaners with asthma'. Occup Environ Med, 72: 757\u0026ndash;763\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang J, Janson C, Gislason T, Gunnbj\u0026ouml;rnsdottir M, Jogi R, Dan Norb\u0026auml;ck (2023) Hans Orru, and. 'Volatile organic compounds (VOC) in homes associated with asthma and lung function among adults in Northern Europe'. Environ Pollut, 321\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZock J-P, Plana E, Jarvis D, Ant\u0026oacute; JM, Hans Kromhout SM, Kennedy N, K\u0026uuml;nzli S, Villani M, Olivieri Kjell Tor\u0026eacute;n, Katja Radon, Jordi Sunyer, Anna Dahlman-Hoglund, Dan Norb\u0026auml;ck, and Manolis Kogevinas. 2007. 'The use of household cleaning sprays and adult asthma: an international longitudinal study'. Am J Respir Crit Care Med, 176: 735\u0026ndash;741\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Characteristics of study sample (N=318)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean (SD) or N (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u0026nbsp;\u003c/strong\u003e/years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e55 (6.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e147 (46.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e171 (53.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrent smoker\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28 (8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFormer smoker\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e150 (47.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAtopy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e132 (52.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e119 (47.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupations (ASCO skill level)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Unemployed/student/retired/housewife\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18 (6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Elementary occupations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13 (4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; All workers/clerks/machine operators\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98 (32.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Technicians\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22 (7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Professionals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e117 (38.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Legislators/senior officials/managers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34 (11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrent asthma\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e49 (15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCOPD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35 (12.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cbr\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Prevalence and characteristics of cleaning products identified by LCA\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eProfile name\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMinimal users\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLight users\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eModerate users\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeavy users\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDescription\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHigh possibility that participants do not use cleaning products at work and at home.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHigher possibilities of using bleach, spray, solvent or acids. \u0026nbsp; \u0026nbsp; \u0026nbsp;Occupational exposure was similar to reference group.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHighest possibilities of using bleach and spray, higher possibilities of using ammonia, solvent and occupational exposure.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMost exposed group, highest possibilities of using bleach, spray and solvent together, higher possibilities of using polish, ammonia, acid and occupational cleaning products.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eN (prevalence)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e80 (25.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e104 (33.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75 (23.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56 (17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45 (56.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e43 (41.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29 (51.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrent smoker (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 (7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8 (7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5 (8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAtopy (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40 (58.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39 (48.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33 (55.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19 (47.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eParticipants who engaged in high exposure occupation to cleaning products (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12 (15.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14 (13.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. The proportions of frequent users (at least once per week) across cleaning product classes\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTypes of cleaning products\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMinimum users\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLighter users\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModerate users\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeavy users\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP values\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBleach\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e25.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e42.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e46.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpray\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e5.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e26.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e29.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e41.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePolish\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e1.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e5.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e16.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupational Chemicals\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e3.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e41.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e26.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e53.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmmonia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e3.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e4.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e12.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSolvent\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e13.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e12.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e41.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAcids\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e28.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e14.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. Adjusted associations* between cleaning products LCA and respiratory outcomes.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRespiratory outcomes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLighter users\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eModerate users\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeavy users\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrent asthma\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.96 (0.36, 2.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.25 (0.46, 3.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.24 (1.19, 8.77)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCOPD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.04 (0.30, 3.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.90 (0.23, 3.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.06 (0.55, 7.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePre-bronchodilator\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(z-score)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFEV\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.14 (-0.45, 0.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.20 (-0.54, 0.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.57 (-0.97, -0.17)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFVC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.17 (-0.46, 0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.23 (-0.59, 0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.46 (-0.82, -0.11)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFEV\u003csub\u003e1\u003c/sub\u003e/FVC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.06 (-0.21, 0.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.08 (-0.22, 0.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.15 (-0.50, 0.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePost-bronchodilator\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(z-score)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFEV\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.01 (--0.32, 0.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.07 (-0.40, 0.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.47 (-0.86, -0.07)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFVC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.15 (-0.45, 0.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.19 (-0.51, 0.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.46 (-0.83, -0.08)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFEV\u003csub\u003e1\u003c/sub\u003e/FVC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.24 (-0.05, 0.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.19 (-0.13, 0.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.04 (-0.33, 0.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*For current asthma outcome, association was adjusted for sex, age, occupations, BMI and current smoking; for lung function outcomes, associations were adjusted for occupation and current smoking.\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-science-and-pollution-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"espr","sideBox":"Learn more about [Environmental Science and Pollution Research](https://www.springer.com/journal/11356)","snPcode":"11356","submissionUrl":"https://submission.nature.com/new-submission/11356/3","title":"Environmental Science and Pollution Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"list: Epidemiology, Air pollution, Pulmonary disease, Asthma, Lung function, COPD, observational studies","lastPublishedDoi":"10.21203/rs.3.rs-7558837/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7558837/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eExposure to cleaning products may harm the lungs, mainly through inhalation. Given increased use of multiple cleaning prducts at work and home, understanding the impacts of their interplay, rather than individual exposures, is critical, but had not been investigated to date. We aim to investigate the cross-sectional association between exposure to cleaning products at home and/or in the workplace and respiratory health. We conducted a cross-sectional analysis of 318 adults from the Melbourne arm of the ECRHS III. Cleaning product exposure was assessed through questionnaires, categorizing participant exposure into seven product groups. Latent Class Analysis was used to identify exposure classes. Adjusted multivariable regression modelled associations between cleaning product classes and respiratory outcomes. We identified four classes of exposure to cleaning products: \u0026ldquo;Minimal users\u0026rdquo;, \u0026ldquo;Light users\u0026ldquo;, \u0026ldquo;Moderate users\u0026rdquo;, \u0026ldquo;Heavy users\u0026rdquo;. The most exposed \u0026ldquo;Heavy user group\u0026rdquo; characterised people using many different cleaning products on a weekly basis (especially bleach, sprays, polish, solvents, acids). This class was associated with increased risks of current asthma (OR: 3.24, 95%CI 1.19\u0026ndash;8.77), and lower post-bronchodilator FEV\u003csub\u003e1\u003c/sub\u003e (z-score: -0.47) and FVC (-0.46) compared with \u0026ldquo;Minimal users\u0026rdquo;.. We found evidence of four distinct cleaning product exposure classes. Frequent use of multiple cleaning products was linked to more asthma and lower lung function, suggesting potential combined effects. These findings highlight the need for cleaning products standards, and asthma care guidelines to mitigate risks associated with cleaning products.\u003c/p\u003e","manuscriptTitle":"Cleaning products and classes associated with poor respiratory health","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-29 14:52:35","doi":"10.21203/rs.3.rs-7558837/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major Revision","date":"2025-12-31T03:06:27+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-10-15T18:11:11+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-15T16:27:44+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Environmental Science and Pollution Research","date":"2025-10-10T11:04:34+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-30T05:08:42+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Science and Pollution Research","date":"2025-09-25T01:48:36+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-science-and-pollution-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"espr","sideBox":"Learn more about [Environmental Science and Pollution Research](https://www.springer.com/journal/11356)","snPcode":"11356","submissionUrl":"https://submission.nature.com/new-submission/11356/3","title":"Environmental Science and Pollution Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"6660bcbd-8da4-427d-8a82-571c6e6ad98e","owner":[],"postedDate":"October 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-30T16:30:48+00:00","versionOfRecord":{"articleIdentity":"rs-7558837","link":"https://doi.org/10.1007/s11356-026-37616-z","journal":{"identity":"environmental-science-and-pollution-research","isVorOnly":false,"title":"Environmental Science and Pollution Research"},"publishedOn":"2026-03-23 16:12:43","publishedOnDateReadable":"March 23rd, 2026"},"versionCreatedAt":"2025-10-29 14:52:35","video":"","vorDoi":"10.1007/s11356-026-37616-z","vorDoiUrl":"https://doi.org/10.1007/s11356-026-37616-z","workflowStages":[]},"version":"v1","identity":"rs-7558837","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7558837","identity":"rs-7558837","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}