Clinical trial NCT06447974: The Barts Charity Children's Environmental Health Clinic
Official title: The Barts Charity Children's Environmental Health Clinic
Study type: INTERVENTIONAL
Overall status: NOT_YET_RECRUITING
Phase: NA
Conditions: Environmental Exposure
Health Behavior
Asthma in Children
Environmental Illness
Keywords: asthma
Air pollution
environmental
Environmental health clinic
Lead sponsor: Queen Mary University of London
Sponsor class: OTHER
Collaborators: name: Barts & The London NHS Trust
First posted: 2024-06-07
Enrollment: 200
Sex: ALL
Minimum age (years): 4
Maximum age (years): 17
Standard ages: CHILD
Accepts healthy volunteers: yes
Allocation: NA
Intervention model: SINGLE_GROUP
Intervention model description: Participants undergo personal exposure monitoring before and after the introduction of mitigation strategies.
Primary purpose: TREATMENT

Brief summary: The study will be based from a newly formed NHS service, the children's environmental health service. Participants will be children with a known chronic respiratory condition. Participants will undergo personal environmental exposure monitoring as well as home environmental assessments, before personalised exposure reports will be provided including a summary of their exposure and advising mitigation strategies based on exposure patterns and behaviours. The monitoring will be repeated after introduction of mitigation strategies. This will allow a comparison of the effectiveness of each method of mitigation.

Detailed description: Data will be collected from multiple sources during the study, including retrospective medical records and results, as well as data recorded as part of the study. These will include the following sources; Medical records from Royal London (including investigation results), Questionnaire responses, clinical interviews at clinic visits, new clinical investigations and home assessments.

These data will be both quantitative and qualitative. The data will be recorded on bespoke electronic databases, which will be securely stored on servers within the Bart's Health/ QMUL, More information on the collection and storage of each type of data can be found below.

Medical records from Royal London: Relevant clinical information and demographics will be extracted from the NHS electronic medical records as baseline information for the assessment in the environmental health clinic. This will be performed by members of the investigative team. Extracted information will include demographics, medical diagnoses, respiratory history, hospital visit history and clinical investigation results. Investigation results may include lung function, FeNO, blood test results, chest x-ray reports and any other relevant results from the child's medical history.

Questionnaires: Participants or their families will complete and return an Environmental Health Questionnaire which was designed for the purposes of the study. Answers to questions from the environmental health questionnaire will be in the form of multiple choice and short answer written questions. The questionnaire will be repeated throughout the participant's involvement in the clinic at designated points. The data from the questionnaires will be recorded in a digital database, will be created for the purpose of the clinic. This database will be stored securely within Barts Health / QMUL servers.

Medical Reviews: At visits in the clinic, interviews of the participants and their families will take place. This will include detailed medical and social history taking by medical sub investigators and a formal physical examination. To improve standardisation of data collected during interviews, a structured proforma will be developed, to be used while the interviews are being conducted. The data collected during these interviews will be recorded in the medical notes, as well as used to create personalised exposure reports.

Clinical investigations will be performed as part of the clinic. This will include blood eosinophils, FeNO, salivary cotinine and custom mould sensitivity. These investigations will be performed by medical members of staff during clinic visits. The results of these tests will be recorded in the medical notes, as well as in the digital database and secure in the servers based at Barts Health

Home assessments: During the period of home monitoring, participants will undergo assessments of their homes, their personal exposure to pollutants and undergo further health monitoring through the monitoring period. The home assessment will review mould and include a custom mould test comparing the child's blood IgG with a scraping from the mould in their home. The assessment of personal exposure will be performed using the Atmotube air quality monitor attached to a backpack (this is not a medical device). This monitor will be kept with the child at home, on their commutes and also at school. The portable air quality monitor measures air concentrations of particulate matter and volatile organic compounds (VOCs), humidity, temperature as well as GPS data and compares this against time. The encrypted anonymous data is then uploaded to a secure API before being stored within secure databases within the Barts health NHS servers. This database is stored securely within protected servers. No personal identifiable data or demographics is shared with Atmo or any other team otuside the clinic team.

After initial data collection and the home monitoring period, the data is collated and analysed by a medical member of the team to create a personal exposure report for each participant. This report will be provided to the participant, saved in the medical records, and used to recommend any appropriate exposure mitigation strategies. Follow up reviews will repeat the monitoring process and update the database, to compare the results before and after mitigation strategies have been introduced.

Eligibility criteria: Inclusion Criteria:

* Parent/Guardian able to provide written informed consent

Referral made by paediatric asthma team

Child aged 4-17 years at the time of consent to study

A diagnosis of a chronic respiratory condition (diagnosis by a medical professional)

Contactable for regular follow up by the research team

Reasonable level of English language

Ability to engage with technology and devices used in the study

Exclusion Criteria:

* Inability to use the tools and devices in the research study

Inability to visit the hospital for the initial hospital visit

Inability to allow home environmental assessment

Primary outcomes:
measure: How effective is a specialist NHS environmental health clinic in reducing exposure to environmental contaminants in children with chronic respiratory disease, and what is the change in health outcomes.
timeFrame: 3 years
Secondary outcomes:
measure: What is the environmental exposure of children attending the environmental health clinic?
timeFrame: 3 years
measure: Are clinical tests such as salivary cotinine, exhaled carbon monoxide or blood eosinophils useful in screening for children who have a high environmental exposure to pollutants?
timeFrame: 3 years
measure: At which locations and times of day are children exposed to the most air pollution?
timeFrame: 3 years
measure: Does exposure to indoor and outdoor air pollution follow a repeated pattern each day?
timeFrame: 3 years
measure: Which factors affect the levels of environmental exposure to pollutants?
timeFrame: 3 years
measure: How does exposure to pollutants affect the health of children and young people with chronic respiratory disease?
timeFrame: 3 years
measure: Which mitigation strategies are effective in reducing the effects of pollution exposure and in which patients are they efficacious?
timeFrame: 3 years
measure: Is an NHS environmental health clinic effective in delivering improvements in respiratory health of children with chronic respiratory disease?
timeFrame: 3 years
Other outcomes:
Locations:
city: London
country: United Kingdom
facility: Queen Mary University of London
Study officials:
affiliation: Queen Mary University of London
name: Charles S Moorcroft, MBChB
role: PRINCIPAL_INVESTIGATOR
References:
citation: Brook RD, Rajagopalan S, Pope CA 3rd, Brook JR, Bhatnagar A, Diez-Roux AV, Holguin F, Hong Y, Luepker RV, Mittleman MA, Peters A, Siscovick D, Smith SC Jr, Whitsel L, Kaufman JD; American Heart Association Council on Epidemiology and Prevention, Council on the Kidney in Cardiovascular Disease, and Council on Nutrition, Physical Activity and Metabolism. Particulate matter air pollution and cardiovascular disease: An update to the scientific statement from the American Heart Association. Circulation. 2010 Jun 1;121(21):2331-78. doi: 10.1161/CIR.0b013e3181dbece1. Epub 2010 May 10.
citation: Kampa M, Castanas E. Human health effects of air pollution. Environ Pollut. 2008 Jan;151(2):362-7. doi: 10.1016/j.envpol.2007.06.012. Epub 2007 Jul 23.
citation: GBD 2016 Risk Factors Collaborators. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2017 Sep 16;390(10100):1345-1422. doi: 10.1016/S0140-6736(17)32366-8.
citation: Sram RJ, Binkova B, Dejmek J, Bobak M. Ambient air pollution and pregnancy outcomes: a review of the literature. Environ Health Perspect. 2005 Apr;113(4):375-82. doi: 10.1289/ehp.6362.
citation: Brugha R, Grigg J. Urban air pollution and respiratory infections. Paediatr Respir Rev. 2014 Jun;15(2):194-9. doi: 10.1016/j.prrv.2014.03.001. Epub 2014 Mar 12.
citation: Gehring U, Wijga AH, Koppelman GH, Vonk JM, Smit HA, Brunekreef B. Air pollution and the development of asthma from birth until young adulthood. Eur Respir J. 2020 Jul 2;56(1):2000147. doi: 10.1183/13993003.00147-2020. Print 2020 Jul.
citation: Lacasana M, Esplugues A, Ballester F. Exposure to ambient air pollution and prenatal and early childhood health effects. Eur J Epidemiol. 2005;20(2):183-99. doi: 10.1007/s10654-004-3005-9.
citation: Li X, Huang S, Jiao A, Yang X, Yun J, Wang Y, Xue X, Chu Y, Liu F, Liu Y, Ren M, Chen X, Li N, Lu Y, Mao Z, Tian L, Xiang H. Association between ambient fine particulate matter and preterm birth or term low birth weight: An updated systematic review and meta-analysis. Environ Pollut. 2017 Aug;227:596-605. doi: 10.1016/j.envpol.2017.03.055. Epub 2017 Apr 28.
citation: Bobak M, Leon DA. The effect of air pollution on infant mortality appears specific for respiratory causes in the postneonatal period. Epidemiology. 1999 Nov;10(6):666-70.
citation: Cai Y, Hansell AL, Granell R, Blangiardo M, Zottoli M, Fecht D, Gulliver J, Henderson AJ, Elliott P. Prenatal, Early-Life, and Childhood Exposure to Air Pollution and Lung Function: The ALSPAC Cohort. Am J Respir Crit Care Med. 2020 Jul 1;202(1):112-123. doi: 10.1164/rccm.201902-0286OC.
citation: Smith RB, Fecht D, Gulliver J, Beevers SD, Dajnak D, Blangiardo M, Ghosh RE, Hansell AL, Kelly FJ, Anderson HR, Toledano MB. Impact of London's road traffic air and noise pollution on birth weight: retrospective population based cohort study. BMJ. 2017 Dec 5;359:j5299. doi: 10.1136/bmj.j5299.
citation: Taussig LM, Wright AL, Holberg CJ, Halonen M, Morgan WJ, Martinez FD. Tucson Children's Respiratory Study: 1980 to present. J Allergy Clin Immunol. 2003 Apr;111(4):661-75; quiz 676. doi: 10.1067/mai.2003.162.
citation: Achakulwisut P, Brauer M, Hystad P, Anenberg SC. Global, national, and urban burdens of paediatric asthma incidence attributable to ambient NO2 pollution: estimates from global datasets. Lancet Planet Health. 2019 Apr;3(4):e166-e178. doi: 10.1016/S2542-5196(19)30046-4. Epub 2019 Apr 11.
citation: Beasley R, Semprini A, Mitchell EA. Risk factors for asthma: is prevention possible? Lancet. 2015 Sep 12;386(9998):1075-85. doi: 10.1016/S0140-6736(15)00156-7.
citation: Mukherjee M, Stoddart A, Gupta RP, Nwaru BI, Farr A, Heaven M, Fitzsimmons D, Bandyopadhyay A, Aftab C, Simpson CR, Lyons RA, Fischbacher C, Dibben C, Shields MD, Phillips CJ, Strachan DP, Davies GA, McKinstry B, Sheikh A. The epidemiology, healthcare and societal burden and costs of asthma in the UK and its member nations: analyses of standalone and linked national databases. BMC Med. 2016 Aug 29;14(1):113. doi: 10.1186/s12916-016-0657-8.
citation: Liang L, Gong P, Cong N, Li Z, Zhao Y, Chen Y. Assessment of personal exposure to particulate air pollution: the first result of City Health Outlook (CHO) project. BMC Public Health. 2019 Jun 7;19(1):711. doi: 10.1186/s12889-019-7022-8.
citation: Evangelopoulos D, Katsouyanni K, Keogh RH, Samoli E, Schwartz J, Barratt B, Zhang H, Walton H. PM2.5 and NO2 exposure errors using proxy measures, including derived personal exposure from outdoor sources: A systematic review and meta-analysis. Environ Int. 2020 Apr;137:105500. doi: 10.1016/j.envint.2020.105500. Epub 2020 Feb 1.
citation: Fan Y, Han Y, Liu Y, Wang Y, Chen X, Chen W, Liang P, Fang Y, Wang J, Xue T, Yao Y, Li W, Qiu X and Zhu T. Biases Arising from the Use of Ambient Measurements to Represent Personal Exposure in Evaluating Inflammatory Responses to Fine Particulate Matter: Evidence from a Panel Study in Beijing, China. Environmental Science & Technology Letters. 2020;7:746-752.
citation: Snyder EG, Watkins TH, Solomon PA, Thoma ED, Williams RW, Hagler GS, Shelow D, Hindin DA, Kilaru VJ, Preuss PW. The changing paradigm of air pollution monitoring. Environ Sci Technol. 2013 Oct 15;47(20):11369-77. doi: 10.1021/es4022602. Epub 2013 Oct 3.
citation: Koehler KA, Peters TM. New Methods for Personal Exposure Monitoring for Airborne Particles. Curr Environ Health Rep. 2015 Dec;2(4):399-411. doi: 10.1007/s40572-015-0070-z.
citation: Branco PT, Alvim-Ferraz MC, Martins FG, Sousa SI. The microenvironmental modelling approach to assess children's exposure to air pollution - A review. Environ Res. 2014 Nov;135:317-32. doi: 10.1016/j.envres.2014.10.002. Epub 2014 Oct 22.
citation: Nieuwenhuijsen MJ, Donaire-Gonzalez D, Foraster M, Martinez D, Cisneros A. Using personal sensors to assess the exposome and acute health effects. Int J Environ Res Public Health. 2014 Aug 6;11(8):7805-19. doi: 10.3390/ijerph110807805.
citation: Nieuwenhuijsen MJ, Donaire-Gonzalez D, Rivas I, de Castro M, Cirach M, Hoek G, Seto E, Jerrett M, Sunyer J. Variability in and agreement between modeled and personal continuously measured black carbon levels using novel smartphone and sensor technologies. Environ Sci Technol. 2015 Mar 3;49(5):2977-82. doi: 10.1021/es505362x. Epub 2015 Feb 9.
citation: Han Y, Chatzidiakou L, Yan L, Chen W, Zhang H, Krause A, Xue T, Chan Q, Liu J, Wu Y, Barratt B, Jones R, Zhu T, Kelly FJ. Difference in ambient-personal exposure to PM2.5 and its inflammatory effect in local residents in urban and peri-urban Beijing, China: results of the AIRLESS project. Faraday Discuss. 2021 Mar 1;226:569-583. doi: 10.1039/d0fd00097c. Epub 2020 Dec 9.
citation: Lim S, Barratt B, Holliday L, Griffiths CJ, Mudway IS. Characterising professional drivers' exposure to traffic-related air pollution: Evidence for reduction strategies from in-vehicle personal exposure monitoring. Environ Int. 2021 Aug;153:106532. doi: 10.1016/j.envint.2021.106532. Epub 2021 Mar 31.
citation: Chatzidiakou L, Krause A, Han Y, Chen W, Yan L, Popoola OAM, Kellaway M, Wu Y, Liu J, Hu M; AIRLESS team; Barratt B, Kelly FJ, Zhu T, Jones RL. Using low-cost sensor technologies and advanced computational methods to improve dose estimations in health panel studies: results of the AIRLESS project. J Expo Sci Environ Epidemiol. 2020 Nov;30(6):981-989. doi: 10.1038/s41370-020-0259-6. Epub 2020 Aug 12.
citation: Ha S, Nobles C, Kanner J, Sherman S, Cho SH, Perkins N, Williams A, Grobman W, Biggio J, Subramaniam A, Ouidir M, Chen Z, Mendola P. Air Pollution Exposure Monitoring among Pregnant Women with and without Asthma. Int J Environ Res Public Health. 2020 Jul 7;17(13):4888. doi: 10.3390/ijerph17134888.
citation: Personal interventions and risk communication on air pollution. Geneva: World Health Organization ; 2020. Licence : CC BY-NC-SA 3.0 IGO.