Reconstructing individual-level exposures in cohort analyses of environmental risks: an example with the UK Biobank.

Recent developments in linkage procedures and exposure modelling offer great prospects for cohort analyses on the health risks of environmental factors. However, assigning individual-level exposures to large population-based cohorts poses methodological and practical problems. In this contribution, we illustrate a linkage framework to reconstruct environmental exposures for individual-level epidemiological analyses, discussing methodological and practical issues such as residential mobility and privacy concerns. The framework outlined here requires the availability of individual residential histories with related time periods, as well as high-resolution spatio-temporal maps of environmental exposures. The linkage process is carried out in three steps: (1) spatial alignment of the exposure maps and residential locations to extract address-specific exposure series; (2) reconstruction of individual-level exposure histories accounting for residential changes during the follow-up; (3) flexible definition of exposure summaries consistent with alternative research questions and epidemiological designs. The procedure is exemplified by the linkage and processing of daily averages of air pollution for the UK Biobank cohort using gridded spatio-temporal maps across Great Britain. This results in the extraction of exposure summaries suitable for epidemiological analyses of both short and long-term risk associations and, in general, for the investigation of temporal dependencies. The linkage framework presented here is generally applicable to multiple environmental stressors and can be extended beyond the reconstruction of residential exposures. IMPACT: This contribution describes a linkage framework to assign individual-level environmental exposures to population-based cohorts using high-resolution spatio-temporal exposure. The framework can be used to address current limitations of exposure assessment for the analysis of health risks associated with environmental stressors. The linkage of detailed exposure information at the individual level offers the opportunity to define flexible exposure summaries tailored to specific study designs and research questions. The application of the framework is exemplified by the linkage of fine particulate matter (PM2.5) exposures to the UK Biobank cohort.

Excess mortality attributed to heat and cold: a health impact assessment study in 854 cities in Europe.

BACKGROUND: Heat and cold are established environmental risk factors for human health. However, mapping the related health burden is a difficult task due to the complexity of the associations and the differences in vulnerability and demographic distributions. In this study, we did a comprehensive mortality impact assessment due to heat and cold in European urban areas, considering geographical differences and age-specific risks. METHODS: We included urban areas across Europe between Jan 1, 2000, and Dec 12, 2019, using the Urban Audit dataset of Eurostat and adults aged 20 years and older living in these areas. Data were extracted from Eurostat, the Multi-country Multi-city Collaborative Research Network, Moderate Resolution Imaging Spectroradiometer, and Copernicus. We applied a three-stage method to estimate risks of temperature continuously across the age and space dimensions, identifying patterns of vulnerability on the basis of city-specific characteristics and demographic structures. These risks were used to derive minimum mortality temperatures and related percentiles and raw and standardised excess mortality rates for heat and cold aggregated at various geographical levels. FINDINGS: Across the 854 urban areas in Europe, we estimated an annual excess of 203 620 (empirical 95% CI 180 882-224 613) deaths attributed to cold and 20 173 (17 261-22 934) attributed to heat. These corresponded to age-standardised rates of 129 (empirical 95% CI 114-142) and 13 (11-14) deaths per 100 000 person-years. Results differed across Europe and age groups, with the highest effects in eastern European cities for both cold and heat. INTERPRETATION: Maps of mortality risks and excess deaths indicate geographical differences, such as a north-south gradient and increased vulnerability in eastern Europe, as well as local variations due to urban characteristics. The modelling framework and results are crucial for the design of national and local health and climate policies and for projecting the effects of cold and heat under future climatic and socioeconomic scenarios. FUNDING: Medical Research Council of UK, the Natural Environment Research Council UK, the EU's Horizon 2020, and the EU's Joint Research Center.

Postnatal exposure to PM2.5 and weight trajectories in early childhood.

BACKGROUND: Inconsistent evidence has assessed the impact of air pollution exposure on children's growth trajectories. We investigated the role of 90-day average postnatal fine particulate matter (PM2.5) exposures by estimating the magnitude of effects at different ages, and the change in child weight trajectory by categories of exposure. METHODS: We obtained weight values from electronic health records at each hospital visit (males = 1859, females = 1601) from birth to 6 years old children recruited into the Boston-based Children's HealthWatch cohort (2009-2014). We applied mixed models, adjusting for individual and maternal confounders using (1) varying-coefficient models allowing for smooth non-linear interaction between age and PM2.5, (2) factor-smooth interaction between age and PM2.5 quartiles. Additionally, we stratified by sex and low birthweight (LBW) status (≤2500 g). RESULTS: Using varying-coefficient models, we found that PM2.5 significantly modified the association between age and weight in males, with a positive association in children younger than 3 years and a negative association afterwards. In boys, for each 10 µg/m3 increase in PM2.5 we found a 2.6% increase (95% confidence interval = 0.8, 4.6) in weight at 1 year of age and a -0.6% (95% confidence interval = -3.9, 2.9) at 5 years. We found similar but smaller changes in females, and no differences comparing growth trajectories across quartiles of PM2.5. Most of the effects were in LBW children and null for normal birthweight children. CONCLUSIONS: This study suggests that medium-term postnatal PM2.5 may modify weight trajectories nonlinearly in young children, and that LBW babies are more susceptible than normal-weight infants.

Use of State Sequence Analysis in Pharmacoepidemiology: A Tutorial.

While state sequence analysis (SSA) has been long used in social sciences, its use in pharmacoepidemiology is still in its infancy. Indeed, this technique is relatively easy to use, and its intrinsic visual nature may help investigators to untangle the latent information within prescription data, facilitating the individuation of specific patterns and possible inappropriate use of medications. In this paper, we provide an educational primer of the most important learning concepts and methods of SSA, including measurement of dissimilarities between sequences, the application of clustering methods to identify sequence patterns, the use of complexity measures for sequence patterns, the graphical visualization of sequences, and the use of SSA in predictive models. As a worked example, we present an application of SSA to opioid prescription patterns in patients with non-cancer pain, using real-world data from Italy. We show how SSA allows the identification of patterns in prescriptions in these data that might not be evident using standard statistical approaches and how these patterns are associated with future discontinuation of opioid therapy.