Air pollution and brain health:defining the research agenda

Purpose of review: The literature on air pollution and brain health is rapidly expanding and it is a universal finding that greater exposure to air pollution is associated with worse outcomes, whatever the measure of brain health used (clinical dementia, neuroimaging correlates, or cognitive impairment). However, there are a number of important questions which the studies currently published are not able to answer: when in the life course does exposure to air pollution most have the most impact?; which pollutant(s) or components are most important?; and since dementia describes a heterogeneous group of conditions, which is most affected by exposure to air pollution? Recent findings: We briefly review and discuss the nine articles which have been published so far in 2018, so recently that they were not included in the four review articles also published this year. We highlight the variation in estimates of air pollution used but the consistency in deriving them from residential address (with or without some knowledge of an individual's previous home locations). Summary: We are now at the stage when the research agenda needs to be agreed and we believe these three questions should be the focus of future research

Heterogeneity of Frailty Trajectories and Associated Factors in the Lothian Birth Cohort 1936

INTRODUCTION: Recent research suggests that the experience of frailty progression may be heterogeneous, with latent subpopulations of older adults following distinct trajectories of frailty. We aimed to investigate this notion and determine whether certain factors are associated with the membership of these subpopulations. METHODS: Data from 5 data waves collected over 12 years in participants of the Lothian Birth Cohort 1936, aged 70 at baseline, were used to derive the frailty index (FI) (NW1 = 1,091, NW5 = 431). These were used in latent class mixed modelling to estimate subpopulations of frailty trajectories. RESULTS: A quadratic latent class mixed model found 3 distinct groupings, which followed a low (61%, n = 632), medium (36%, n = 368), or high (3%, n = 28) FI trajectory. Each grouping had different intercepts and slopes, with the high grouping following the steepest trajectory indicating a rapid increase in frailty. Findings showed that in general, those in the low grouping were younger, had higher education, higher age 11 cognitive ability, and were from a higher social class than those in the medium and high groupings. DISCUSSION/CONCLUSION: Our findings demonstrate heterogeneity in frailty trajectories over 12 years in individuals aged 70 years at baseline. Membership of higher frailty trajectory groupings was associated with lower social class, less education, and lower childhood cognitive ability, indicating the potential for future interventions to target individuals who are at the greatest risk of belonging to the high frailty trajectory. Future research is required to continue this line of inquiry by exploring other risk and protective factors, and importantly, to assess whether it is possible to realign an individual's membership to a less detrimental grouping of frailty trajectory