Measuring and modelling perceptions of the built environment for epidemiological research using crowd-sourcing and image-based deep learning models.

BACKGROUND: Perceptions of the built environment, such as nature quality, beauty, relaxation, and safety, may be key factors linking the built environment to human health. However, few studies have examined these types of perceptions due to the difficulty in quantifying them objectively in large populations. OBJECTIVE: To measure and predict perceptions of the built environment from street-view images using crowd-sourced methods and deep learning models for application in epidemiologic studies. METHODS: We used the Amazon Mechanical-Turk crowdsourcing platform where participants compared two street-view images and quantified perceptions of nature quality, beauty, relaxation, and safety. We optimized street-view image sampling methods to improve the quality and resulting perception data specific to participants enrolled in the Washington State Twin Registry (WSTR) health study. We used a transfer learning approach to train deep learning models by leveraging existing image perception data from the PlacePulse 2.0 dataset, which includes 1.1 million image comparisons, and refining based on new WSTR perception data. Resulting models were applied to WSTR addresses to estimate exposures and evaluate associations with traditional built environment measures. RESULTS: We collected over 36,000 image comparisons and calculated perception measures for each image. Our final deep learning models explained 77.6% of nature quality, 68.1% of beauty, 72.0% of relaxation, and 64.7% of safety in pairwise image comparisons. Applying transfer learning with the new perception labels specific to the WSTR yielded an average improvement of 3.8% for model performance. Perception measures were weakly to moderately correlated with traditional built environment exposures for WSTR participant addresses; for example, nature quality and NDVI (r = 0.55), neighborhood area deprivation (r = -0.16), and walkability (r = -0.20), respectively. SIGNIFICANCE: We were able to measure and model perceptions of the built environment optimized for a specific health study. Future applications will examine associations between these exposure measures and mental health in the WSTR. IMPACT STATEMENT: Built environments influence health through complex pathways. Perceptions of nature quality, beauty, relaxation and safety may be particularly import for understanding these linkages, but few studies to-date have examined these perceptions objectively for large populations. For quantitative research, an exposure measure must be reproducible, accurate, and precise--here we work to develop such measures for perceptions of the urban environment. We created crowd-sourced and image-based deep learning methods that were able to measure and model these perceptions. Future applications will apply these models to examine associations with mental health in the Washington State Twin Registry.

Correction: I2/TBHP mediated diastereoselective synthesis of spiroaziridines.

Correction for 'I2/TBHP mediated diastereoselective synthesis of spiroaziridines' by Kizhakkan Thiruthi Ashitha et al., Org. Biomol. Chem., 2020, 18, 1588-1593, DOI: 10.1039/C9OB02711D.

I2/TBHP mediated diastereoselective synthesis of spiroaziridines.

Eventhough spiroheterocycles are considered as emerging drug candidates, synthesis of spiroaziridines has not been well explored so far. Herein, we disclose an efficient I2/TBHP mediated diastereoselective synthesis of N-alkyl spiroaziridines from primary amines and easily accessible α,ß-unsaturated ketones. The reaction is also compatible for the synthesis of 2-aroylaziridines.

Iodized Salt Consumption and its Association with Intelligence Quotient (IQ) Among 6-12 years Age Group Children in Bihar.

OBJECTIVES: To estimate the proportion of households using adequately iodized salt, total goitre rate and intelligence quotient (IQ) and to assess association, if any, between consumption of iodized salt and intelligence quotient of children aged 6-12 y in the selected districts of Bihar. METHODS: Community based cross-sectional study was conducted in three districts of Bihar by using cluster sampling technique. RESULTS: Consumption of iodized salt was 73.5% out of 1263 households surveyed and the prevalence of goitre among children was 2.9%. The mean IQ of study population was 82.6 and it was 9 points lower in children consuming inadequately iodized salt in comparison to children consuming adequately iodized salt. Presence of goitre, inadequately iodized salt consumption and increasing age were the factors which were significant predictors of low IQ level. CONCLUSIONS: The prevalence of goitre has declined from the past but the target of iodized salt consumption has not yet achieved in these districts. This study reinforces the belief that IQ in children is linked to iodine.