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Background: We have developed an open-source ALgorithm for Generating Address Exposures (ALGAE) that cleans residential address records to construct address histories and assign spatially-determined exposures to cohort participants. The first application of this algorithm was to construct prenatal and early life air pollution exposure for individuals of the Avon Longitudinal Study of Parents and Children (ALSPAC) in the South West of England, using previously estimated particulate matter ≤10  µm (PM10) concentrations.Methods: ALSPAC recruited 14 541 pregnant women between 1991 and 1992. We assigned trimester-specific estimated PM10 exposures for 12 752 pregnancies, and first year of life exposures for 12 525 births, based on maternal residence and residential mobility.Results: Average PM10 exposure was 32.6  µg/m3 [standard deviation (S.D.) 3.0  µg/m3] during pregnancy and 31.4 µg/m3 (S.D. 2.6  µg/m3) during the first year of life; 6.7% of women changed address during pregnancy, and 18.0% moved during first year of life of their infant. Exposure differences ranged from -5.3  µg/m3 to 12.4  µg/m3 (up to 26% difference) during pregnancy and -7.22  µg/m3 to 7.64  µg/m3 (up to 27% difference) in the first year of life, when comparing estimated exposure using the address at birth and that assessed using the complete cleaned address history. For the majority of individuals exposure changed by <5%, but some relatively large changes were seen both in pregnancy and in infancy.Conclusions: ALGAE provides a generic and adaptable, open-source solution to clean addresses stored in a cohort contact database and assign life stage-specific exposure estimates with the potential to reduce exposure misclassification. [ABSTRACT FROM AUTHOR]

Background Area-based initiatives that include a focus on community empowerment are increasingly being seen as potentially an important way of improving health and reducing inequalities. However, there is little empirical evidence on the pathways between communities having more control and health outcomes. Purpose To identify pathways to health improvement in a community-led area-based community empowerment initiative. Methods Longitudinal data on mental health, community control, area belonging, satisfaction, social cohesion and safety were collected over two time points, 6 months apart from 48 participants engaged in the Big Local programme, England. Qualitative comparative analysis (QCA) was used to explore pathways to health improvement. Results There was no clear single pathway that led to mental health improvement but positive changes in 'neighbourhood belonging' featured in 4/5 health improvement configurations. Further, where respondents experienced no improvement in key social participation/control factors, they experienced no health improvement. Conclusion This study demonstrates a potential pathway between an improvement in 'neighbourhood belonging' and improved mental health outcomes in a community empowerment initiative. Increasing neighbourhood belonging could be a key target for mental health improvement interventions. [ABSTRACT FROM AUTHOR]