Green space exposure and blood DNA methylation at birth and in childhood - A multi-cohort study.

Green space exposure has been associated with improved mental, physical and general health. However, the underlying biological mechanisms remain largely unknown. The aim of this study was to investigate the association between green space exposure and cord and child blood DNA methylation. Data from eight European birth cohorts with a total of 2,988 newborns and 1,849 children were used. Two indicators of residential green space exposure were assessed: (i) surrounding greenness (satellite-based Normalized Difference Vegetation Index (NDVI) in buffers of 100 m and 300 m) and (ii) proximity to green space (having a green space ≥ 5,000 m2 within a distance of 300 m). For these indicators we assessed two exposure windows: (i) pregnancy, and (ii) the period from pregnancy to child blood DNA methylation assessment, named as cumulative exposure. DNA methylation was measured with the Illumina 450K or EPIC arrays. To identify differentially methylated positions (DMPs) we fitted robust linear regression models between pregnancy green space exposure and cord blood DNA methylation and between cumulative green space exposure and child blood DNA methylation. Two sensitivity analyses were conducted: (i) without adjusting for cellular composition, and (ii) adjusting for air pollution. Cohort results were combined through fixed-effect inverse variance weighted meta-analyses. Differentially methylated regions (DMRs) were identified from meta-analysed results using the Enmix-combp and DMRcate methods. There was no statistical evidence of pregnancy or cumulative exposures associating with any DMP (False Discovery Rate, FDR, p-value < 0.05). However, surrounding greenness exposure was inversely associated with four DMRs (three in cord blood and one in child blood) annotated to ADAMTS2, KCNQ1DN, SLC6A12 and SDK1 genes. Results did not change substantially in the sensitivity analyses. Overall, we found little evidence of the association between green space exposure and blood DNA methylation. Although we identified associations between surrounding greenness exposure with four DMRs, these findings require replication.

How do schools influence the emotional and behavioural health of their pupils? A multi-level analysis of 135 schools in the Born in Bradford inner city multi-ethnic birth cohort.

PURPOSE: To estimate variation in emotional and behavioural problems between primary schools in Bradford, an ethnically diverse and relatively deprived city in the UK. METHODS: We did a cross-sectional analysis of data collected from 2017 to 2021 as part of the 'Born In Bradford' birth cohort study. We used multilevel linear regression in which the dependent variable was the Strengths and Difficulties Questionnaire (SDQ) total score, with a random intercept for schools. We adjusted for pupil-level characteristics including age, ethnicity, socioeconomic status, and parental mental health. RESULTS: The study included 5,036 participants from 135 schools. Participants were aged 7-11 years and 56% were of Pakistani heritage. The mean SDQ score was 8.84 out of a maximum 40. We estimated that the standard deviation in school-level scores was 1.41 (95% CI 1.11-1.74) and 5.49% (95% CI 3.19-9.37%) of variation was explained at school level. After adjusting for pupil characteristics, the standard deviation of school-level scores was 1.04 (95% CI 0.76-1.32) and 3.51% (95% CI 1.75-6.18%) of variation was explained at school level. Simulation suggested that a primary school with 396 pupils at the middle of the distribution has 63 pupils (95% CI 49-78) with a 'raised' SDQ score of 15 + /40; and shifting a school from the lower to the upper quartile would prevent 26 cases (95% CI 5-46). CONCLUSION: The prevalence of emotional and behavioural problems varies between schools. This is partially explained by pupil characteristics; though residual variation in adjusted scores may suggest that schools have a differential impact on mental wellbeing.