B4353 - Associations between prenatal urban environment and cardiometabolic health from childhood to adolescence - 19/06/2023

B number: 
B4353
Principal applicant name: 
Wen Lun Yuan | INSERM, UMR1153 CRESS (France)
Co-applicants: 
Ahmed Elhakeem, Dr, Ana Luiza Goncalves Soares, Dr, Nicholas John Timpson, Pr, Barbara Heude, Dr, Janine Felix, Dr
Title of project: 
Associations between prenatal urban environment and cardiometabolic health from childhood to adolescence
Proposal summary: 

Living in an urbanized environment undeniably leads to more exposure to urban environmental exposures. Previous studies conducted on urban health were mostly focused on air pollution, while the urban environment is also characterized by its built environment and access to natural spaces. Recently, there is a surging interest to better understand the interplay of different environmental factors that define the urban environment and its effect on children health. Living in a more urbanized environment has been associated with greater adiposity and higher blood pressure in children. Importantly, child cardiometabolic health parameters were mostly investigated individually, while they are intercorrelated. Two approaches have been used to study child cardiometabolic health, a clustering method and a risk score.

Impact of research: 
Findings from this work will be published into 1 to 2 papers and eventually be presented in an international congress.
Date proposal received: 
Tuesday, 6 June, 2023
Date proposal approved: 
Tuesday, 13 June, 2023
Keywords: 
Epidemiology, Diabetes, Hypertension, Obesity, Pregnancy - e.g. reproductive health, postnatal depression, birth outcomes, etc., Computer simulations/modelling/algorithms, Statistical methods, Biomarkers - e.g. cotinine, fatty acids, haemoglobin, etc., Birth outcomes, Offspring, Sex differences, Statistical methods, Blood pressure, BMI, Cardiovascular, Cohort studies - attrition, bias, participant engagement, ethics, Environment - enviromental exposure, pollution, Growth, Metabolic - metabolism, Methods - e.g. cross cohort analysis, data mining, mendelian randomisation, etc.