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Supervisors: Dr Pia Hardelid, Dr Graziella Favarato, Professor Bianca De Stavola
What is the association between exposure to air pollution and adverse housing conditions, and viral respiratory infections in young children?
Background:
Respiratory infections, including bronchiolitis, croup and pneumonia, are the most common reason for hospital admission among children <5 years in the UK.(1) The COVID19 pandemic has highlighted the stark socio-economic inequalities in viral respiratory infection risk.(2) These inequalities have also been observed for other viral infections in children.(3) A number of studies have linked exposure to outdoor air pollution and adverse housing conditions, such as overcrowding or indoor air pollution, to a higher risk of developing severe symptoms of respiratory infections in young children.(4, 5) However, their relative contribution to socio-economic inequalities in respiratory infection risk has not been assessed in a UK context. In particular, there is a dearth of data regarding if and how exposure to air pollution and adverse housing conditions during pregnancy and early life differentially affect the risk of specific viruses, such as SARS-CoV-2, respiratory syncytial virus (RSV) and influenza in children.
Aims/Objectives:
The aim of this PhD is to determine the association between outdoor air pollution, adverse housing conditions, and the incidence of viral respiratory infections in young children, focusing particularly on SARS-CoV-2 and RSV.
The specific objectives are to:
1) establish the association between exposure to ambient air pollution and adverse housing conditions during pregnancy and early childhood, and the incidence of specific respiratory viral infections in early childhood.
2) determine the extent to which exposure to outdoor air pollution and adverse housing conditions explain socio-economic inequalities in the incidence of respiratory viruses and associated hospital admissions in young children.
3) identify specific subgroups of children who are particularly vulnerable to respiratory viral infections following exposure to outdoor air pollution and adverse housing conditions.
Methods:
The student will have a unique opportunity to use data from national birth cohorts, including data from all children born in England in 2005-2014, and in Scotland 1997-2020, created via linkage between civil registration, maternity, public health laboratory surveillance and hospital admission datasets. These datasets are being further linked to Census data on housing conditions and socio-economic position, and small-area level data on ambient air pollution and building characteristics as part of the Air Pollution, housing and respiratory tract Infections in Children: NatIonal birth Cohort (PICNIC) study (https://www.ucl.ac.uk/child-health/picnic-study). The student will use a number of statistical modelling techniques to examine the association between air pollution, housing characteristics and the risk of viral infections and related admissions in children, calculate population attributable fractions for ambient air pollution and adverse housing exposures, and use causal mediation analyses to explore the mechanisms through which housing and air pollution influences the risk of infant viral respiratory infections.
This is an excellent opportunity for a student with a quantitative background (for example an MSc in statistics, epidemiology or demography) to hone their skills in using large, linked administrative health and environmental datasets for child health research. The student will be based in the Child Health Informatics Group (CHIG), a diverse and friendly group of data science researchers, and work closely with the PICNIC research team and partners. There will be opportunity to specialise in specific areas and methodology for environmental health research.
References:
1. NHS Digital. Hospital Admitted Patient Care Activity, 2017-18 2018 [Available from: https://tinyurl.com/y8w8lm5y.
2. Broad J, Forman J, Brighouse J, Sobande A, McIntosh A, Watterson C, et al. Post-COVID-19 paediatric inflammatory multisystem syndrome: association of ethnicity, key worker and socioeconomic status with risk and severity. Archives of Disease in Childhood. 2021:archdischild-2020-320388.
3. Lewis K, De Stavola B, Hardelid P. Is socioeconomic position associated with bronchiolitis seasonality? A cohort study. Journal of Epidemiology and Community Health. 2020:jech-2019-213056.
4. MacIntyre EA, Gehring U, Molter A, Fuertes E, Klumper C, Kramer U, et al. Air pollution and respiratory infections during early childhood: an analysis of 10 European birth cohorts within the ESCAPE Project. Environ Health Perspect. 2014;122(1):107-13.
5. Colosia A, Masaquel A, Hall C, Barrett A, Mahadevia P, Yogev R. Residential crowding and severe respiratory syncytial virus disease among infants and young children: A systematic literature review. BMC Infect Dis. 2012;12:95-.