Background: Structured life course modelling approaches (SLCMA) have been developed to understand how exposures across the lifespan relate to later health, but have primarily been restricted to single exposures. As multiple exposures can jointly impact health, here we: i) demonstrate how to extend SLCMA to include exposure interactions; ii) conduct a simulation study investigating the performance of these methods; and iii) apply these methods to explore associations of access to green space, and its interaction with socioeconomic position, with child cardiometabolic health. Methods: We used three methods, all based on lasso regression, to select the most plausible life course model: visual inspection, information criteria and cross-validation. The simulation study assessed the ability of these approaches to detect the correct interaction term, while varying parameters which may impact power (e.g., interaction magnitude, sample size, exposure collinearity). Methods were then applied to data from a UK birth cohort. Results: There were trade-offs between false negatives and false positives in detecting the true interaction term for different model selection methods. Larger sample size, lower exposure collinearity, centering exposures, continuous outcomes and a larger interaction effect all increased power. In our applied example we found little-to-no association between access to green space, or its interaction with socioeconomic position, and child cardiometabolic outcomes. Conclusions: Incorporating interactions between multiple exposures is an important extension to SLCMA. The choice of method depends on the researchers' assessment of the risks of under- vs over-fitting. These results also provide guidance for improving power to detect interactions using these methods.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9901056

Incorporating interactions into structured life course modelling approaches: A simulation study and applied example of the role of access to green space and socioeconomic position on cardiometabolic health

Studies evaluating the benefits and risks of green spaces on children's health are scarce. The present study aimed to examine the associations between exposure to green spaces during pregnancy and early childhood with respiratory, cardiometabolic, and neurodevelopmental outcomes in school-age children. We performed an Individual-Participant Data (IPD) meta-analysis involving 35,000 children from ten European birth cohorts across eight countries. For each participant, we calculated residential Normalized Difference Vegetation Index (NDVI) within a 300 m buffer and the linear distance to green spaces (meters) during prenatal life and childhood. Multiple harmonized health outcomes were selected: asthma and wheezing, lung function, body mass index, diastolic and systolic blood pressure, non-verbal intelligence, internalizing and externalizing problems, and ADHD symptoms. We conducted a two-stage IPD meta-analysis and evaluated effect modification by socioeconomic status (SES) and sex. Between-study heterogeneity was assessed via random-effects meta-regression. Residential surrounding green spaces in childhood, not pregnancy, was associated with improved lung function, particularly higher FEV1 (β = 0.06; 95 %CI: 0.03, 0.09 I2 = 4.03 %, p < 0.001) and FVC (β = 0.07; 95 %CI: 0.04, 0.09 I2 = 0 %, p < 0.001) with a stronger association observed in females (p < 0.001). This association remained robust after multiple testing correction and did not change notably after adjusting for ambient air pollution. Increased distance to green spaces showed an association with lower FVC (β = -0.04; 95 %CI: -0.07, -0.02, I2 = 4.8, p = 0.001), with a stronger effect in children from higher SES backgrounds (p < 0.001). No consistent associations were found between green spaces and asthma, wheezing, cardiometabolic, or neurodevelopmental outcomes, with direction of effect varying across cohorts. Wheezing and neurodevelopmental outcomes showed high between-study heterogeneity, and the age at outcome assessment was only associated with heterogeneity in internalizing problems.. This large European meta-analysis suggests that childhood exposure to green spaces may lead to better lung function. Associations with other respiratory outcomes and selected cardiometabolic and neurodevelopmental outcomes remain inconclusive.

Green spaces and respiratory, cardiometabolic, and neurodevelopmental outcomes: An individual-participant data meta-analysis of &gt;35.000 European children

Background: International sharing of cohort data for research is important and challenging. The LifeCycle project aimed to harmonise data across birth cohorts and develop methods for efficient federated analyses of early life stressors on offspring outcomes. Aim: To explore feasibility of federated analyses of associations between four different types of pregnancy exposures (maternal education, area deprivation, proximity to green space and gestational diabetes) with offspring BMI from infancy to 17 years. Methods: We used harmonised exposure and outcome data from 17 cohorts (n=200,650 mother-child pairs) from the EU Child Cohort Network. For each child, we derived BMI at five age periods: (i) 0-1 years, (ii) 2-3, (iii) 4-7, (iv) 8-13 and (v) 14-17 years. Associations were estimated using linear regression via one-stage individual participant data meta-analysis using the federated analysis platform DataSHIELD. Results: Associations between lower maternal education and higher child BMI emerged from age 4 years and increased with age (difference in BMI z-score comparing low with high education age 0-1 years = 0.02 [95% CI 0.00, 0.03], 2-3 years = 0.01 [CI -0.02, 0.04], 4-7 years = 0.14 [CI 0.13, 0.16], 8-13 years = 0.22 [CI 0.20, 0.24], 14-17 years = 0.20 [CI 0.16, 0.23]). A similar pattern was found for area deprivation. Gestational diabetes was positively associated with BMI from 8 years (8-13 years = 0.17 [CI 0.10, 0.24], 14-17 years = 0.012 [CI -0.13, 0.38]) but not at younger ages. The normalised difference vegetation index measure of maternal proximity to green space was weakly associated with higher BMI in the first year of life but not at older ages. Conclusions: Associations between maternal education, area-based socioeconomic position and GDM with BMI increased with age. Maternal proximity to green space was not associated with offspring BMI, other than a weak association in infancy. Opportunities and challenges of cross-cohort federated analyses are discussed.

Associations of maternal education, area deprivation, proximity to greenspace during pregnancy and gestational diabetes with Body Mass Index from early childhood to early adulthood: A proof-of-concept federated analysis in seventeen birth cohorts

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Associations of maternal education, area deprivation, proximity to greenspace during pregnancy and gestational diabetes with Body Mass Index from early childhood to early adulthood: A proof-of-concept federated analysis in seventeen birth cohorts