Air Pollution, housing and respiratory tract Infections in Children: NatIonal birth Cohort study (PICNIC)

Lead Research Organisation: University College London
Department Name: Institute of Child Health


What is this research project about?

We will investigate to what extent exposure to air pollution during pregnancy and the first five years of life and poor housing conditions (such as overcrowding and damp/mould) contribute to hospital admissions for respiratory tract infections (RTIs) in children less than five years old.

Why are we doing this research?

RTIs, including bronchiolitis, pneumonia and croup, are the most common reason for hospital admission in young children in the UK. These admissions are stressful for children, their parents and costly for the National Health Service (NHS). Being admitted to hospital with an RTI during the first few years of life is also associated with the development of chronic respiratory problems, such as asthma, in later childhood. Previous research has found that children from poor backgrounds are more likely to need an RTI admission, but it is not clear which aspects of children's living conditions make the largest contribution to RTI hospital admissions. In this study, we will examine whether exposure to air pollution in the womb or during early childhood, and poor housing conditions are associated with a child's risk of being admitted to hospital with an RTI. Also, we will look at how many RTI admissions could be prevented in the UK if we reduced air pollution and/or improved housing conditions for families with young children.

How are we going to do it?

We will use data collected from birth certificates, linked to maternity records and hospital admission data for all children born in England between 2005 and 2014, and Scotland between 1997 and 2019: 8 million children in total. We will link in data about children's air pollution exposure during pregnancy and childhood, building characteristics, and information about housing and socio-economic background from the 2011 Census. All data will be kept on secure servers and linked using methods that protect the identities of mothers and children.

We will use these data to examine whether exposure to air pollution and poor housing conditions are associated with an increased risk of being admitted to hospital with an RTI during the first five years of life. We will use statistical methods that allow us to take into account whether children have other underlying risk factors for RTI hospital admissions, such as chronic health problems. We will also make sure that other researchers can access these datasets to carry out maternal and child health research in the future.

Technical Summary

Respiratory tract infections (RTIs) are the most common reason for hospital admissions in children under five in the UK. We aim to quantify the extent to which in-utero, infant and childhood exposure to air pollution (AP), and adverse housing conditions (including overcrowding and damp/mould) are associated with the risk of RTI admissions in children less than 5 years old.

We will use national administrative data birth cohorts including all children born in England in 2005-2014, and in Scotland 1997-2019, created via linkage between vital statistics, maternity and hospital admission datasets. We will further enhance these cohorts via linkage to Census 2011 data from mothers and their partners on housing conditions and socio-economic position, and small-area level data on AP and building characteristics. Our specific objectives are to:

1) Estimate the association between long-term exposure to ambient AP during pregnancy and infancy and the rate of RTI admissions in infants
2) Derive variables indicating adverse housing conditions (eg overcrowding, indoor air pollution, damp/mould) and estimate the association between housing exposures and infant RTI admissions
3) Based on the outcomes of analyses for objectives 1) and 2), estimate the relative contribution of AP and adverse housing conditions on infant RTI admissions
4) Estimate the relative contribution of AP exposure during pregnancy, infancy and early childhood and adverse housing conditions on RTI admissions in children aged less than five years
5) Establish the linked administrative data birth cohorts as resources for maternal and child health research

Our results will inform policy makers, charities and parents about the relative contribution of AP exposure during pregnancy, infancy and early childhood and housing conditions to RTI admissions in children. Our legacy will include the two national birth cohorts, which will be made available to other researchers.

Planned Impact

RTIs are the most common reason for being admitted to hospital among children under 5 years in the UK, with over 195,000 children admitted annually. These admissions are costly: the annual bill for NHS England due to bronchiolitis alone has been estimated at £84 million. Due to their seasonal nature, RTI admissions cause pressure on accident and emergency departments, and acute assessment and paediatric wards, during the winter.

Our results therefore have potential to improve the respiratory health of children and the environments in which they grow up, and reduce health inequalities in early life. A reduction in RTI admissions will also reduce stress for parents and costs for the NHS. This study therefore has potential to impact on a number of different stakeholders:

Researchers in public, respiratory and maternal and child health: In the short term, researchers in these fields will benefit both from the research findings, and from the national administrative data birth cohorts, linked to Census and small-area level exposure data, which will be made available to other research groups.

Local authorities, housing associations and NHS organisations: Local authorities across England and Scotland are responsible for housing, and reviewing and assessing local air quality. English Local Authorities and Scottish Health Boards are also responsible for monitoring and improving public health in the local area. This project will provide information on the relative importance of risk factors including overcrowding and air pollution to common childhood hospital admissions, providing a sound evidence base for prioritising spending locally in order to improve childhood respiratory health. We will ensure our study results are relevant to local policy makers by carrying out subnational analyses where possible.

Central government (including the Scottish Government, Homes England, Public Health England, Department of Health, NHS Health Scotland): Our findings will provide evidence for national policies to improve children's health, reduce health inequalities and suggest methods for monitoring policy impact at national and local level.

Data providers (including Office for National Statistics, National Records for Scotland and NHS Digital): In the short-to-medium term, the project will identify the Census variables that are most strongly associated with young children's health and therefore need to be captured through other administrative data sources when the Census is phased out after 2021. Our study will also emphasise the utility and importance of linking datasets from different data providers for health research, thereby motivating data sharing and improved access to linked datasets for researchers.

Parents and voluntary sector organisations: This project will provide parents with information about the relative contribution of adverse housing conditions and air pollution to RTI hospital admissions in children. This evidence base can empower parents and voluntary sector organisations to push for improvements in local environments and housing quality.

Research staff & lecturers employed on the project: In the short term, this project will build capacity for data linkage, governance, and administrative data analysis for the research fellow and the data manager working on the project. The three lecturers (PH, TC and AM) leading the project will develop collaborations with senior experts (co-Is and collaborators). This project will therefore contribute to health data science capacity in the UK.


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