Estimating the impact of urban environmental exposures on trajectories of child and adolescent mental health

BACKGROUND

Urban noise exposures affect millions of people in the UK. Environmental noise exposures have been associated with 1000 premature deaths, 6000 cases of heart disease and 750 000 cases of sleep disturbance [1]. Noise can increase stress hormone levels - over time, increased stress and disrupted sleep can lead to pro-inflammatory responses in the body which poses a risk for cardiovascular disease and diabetes [2].

There is established evidence on the relationship between environmental noise and poor mental health outcomes in adults [3,4], and children's reading comprehension [5]. However, more evidence is required regarding young people's mental health, the effect of different noise sources and urban design features. Greater use of longitudinal data on this topic is required to establish temporality and hence provide evidence of causality.

OBJECTIVES

Investigate how the source, setting and time frame of noise exposure, access to greenspace and housing quality influence trajectories of mental health conditions. METHODS 2 cohort datasets will be used for the analysis: - NIHR funded ORiEL study (Olympic Regeneration in East London) - 2254 adolescents from 25 schools in East London [6].

- CLEVER (Cohort for research into Living EnVironments and hEalth in children) ADRUK-funded e-cohort - 11 million children in England, generated using linked administrative data. This project has 2 main methodological aspects:

1. Environmental modelling - the MRC funded Longitudinal Linkage Collaboration (LLC) methodology will be used to model environmental exposures for the ORiEL study participants. The LLC has estimated a range of exposures using a common data standard in 24 UK cohorts, so this can be used as an input into exposure models.

This will inform the modelling approach and address residential mobility in the data set. The ORiEL study has longitudinal data on young people's mental health and wellbeing, and this modelling will link environmental data on the school, home and neighbourhood environments.

2. Multilevel epidemiological and statistical analysis - examine associations between environmental exposures and mental health trajectories, quantify effects and provide evidence of the statistical strength of these associations. The effect measures calculated will be adjusted for confounding factors.

Evidence generated will be used to inform environmental and health impact assessments, planning processes for urban design, and UK policy for children and young people's environments.

Doctoral level skills and training to be gained during this studentship (from the 2017 BBSRC and MRC review of vulnerable skills and capacities) - Working with large datasets in epidemiology - data interpretation, storage, programming and analysis - Data linkage using the MRC LLD methodology - Statistical modelling and environmental modelling

REFERENCES 1.European Environment Agency, 2020. Environmental Noise in Europe Report 2.Medic G et al, 2017. Short- and long-term health consequences of sleep disruption. Nat Sci Sleep. 9:151-161

3.Clark et al, 2020. Evidence for environmental noise effects on health for the United Kingdom Policy Context: A systematic review of the effects of environmental noise on mental health, wellbeing, quality of life, cancer, dementia, birth, reproductive outcomes and cognition. Int J Environ Res Public Health. 17(2): 393.

4.Hegewald et al, 2020. Traffic noise and mental health: A systematic review and meta- analysis. Int J Environ Res Public Health. 17(17): 6175.

5.Clark et al, 2021. A meta-analysis of the association of aircraft noise at school on children's reading comprehension and psychological health for use in health impact assessment. Journal of Environmental Psychology, 76, 101646.

6.Cummins S et al, 2018. The effects of the London 2012 Olympics and related urban regeneration on physical and mental health: the ORiEL mixed-methods evaluation of a natural experiment. Public Health Resea