Longitudinal deprivation trajectories and risk of cardiovascular disease in New Zealand

We used longitudinal information on area deprivation status to explore the relationship between residential-deprivation mobility and Cardiovascular Disease (CVD). Data from 2,418,397 individuals who were: enrolled in any Primary Health Organisation within New Zealand (NZ) during at least 1 of 34 calendar quarters between 1st January 2006 and 30th June 2014; aged between 30 and 84 years (inclusive) at the start of the study period; had no prior history of CVD; and had recorded address information were analysed. Including a novel trajectory analysis, our findings suggest that movers are healthier than stayers. The deprivation characteristics of the move have a larger impact on the relative risk of CVD for younger movers than for older movers. For older movers any kind of move is associated with a decreased risk of CVD

Identifying how COVID-19-related misinformation reacts to the announcement of the UK national lockdown: An interrupted time-series study

COVID-19 is unique in that it is the first global pandemic occurring amidst a crowded information environment that has facilitated the proliferation of misinformation on social media. Dangerous misleading narratives have the potential to disrupt ‘official’ information sharing at major government announcements. Using an interrupted time-series design, we test the impact of the announcement of the first UK lockdown (8–8.30 p.m. 23 March 2020) on short-term trends of misinformation on Twitter. We utilise a novel dataset of all COVID-19-related social media posts on Twitter from the UK 48 hours before and 48 hours after the announcement (n = 2,531,888). We find that while the number of tweets increased immediately post announcement, there was no evidence of an increase in misinformation-related tweets. We found an increase in COVID-19-related bot activity post-announcement. Topic modelling of misinformation tweets revealed four distinct clusters: ‘government and policy’, ‘symptoms’, ‘pushing back against misinformation’ and ‘cures and treatments’

Differences in the risk of cardiovascular disease for movers and stayers in New Zealand: a survival analysis

Objectives: To explore if risk of cardiovascular disease (CVD) for participants who moved before their first CVD event is higher than for stayers, and examine whether the relationship is moderated by ethnicity. Methods: The sample comprised of 2,068,360 New Zealand (NZ) residents enrolled in any Primary Health Organisation, aged between 30-84 years, had complete demographic information, and no prior history of CVD. Cox proportional regression was used to compare CVD risk between movers and stayers. The analysis was conducted for the whole sample and stratified by ethnicity. Results: The combined analysis suggested movers have a lower risk of CVD than stayers. This is consistent for all ethnic groups with some variation according to experience of deprivation change following residential mobility. Conclusions: Although mobile groups may have a higher risk of CVD than immobile groups overall, risk of CVD in the period following a residential mobility event is lower than for stayers. Results are indicative of a short-term healthy migrant effect comparable to that observed for international migrants

Progress in the study of health inequalities and selective migration: Mobilising the new mobilities paradigm

This paper seeks to deepen understandings of the relations between health inequalities and migration, with a particular emphasis on health-selective migration. Papers in this journal have urged for a more nuanced consideration of connections between migration and health but these have not seen-through how to combine understandings of health and migration to better theorise their relations. A strong theoretical basis regarding the politics of mobilities can help say more of the structural factors shaping health-selective migration and therefore, changing health gradients in a population

Defining distance thresholds for migration research

There exists a large body of research focused on migration distance, where migration is either the outcome of interest or used as an input variable to model something else. However, there is little consistency in the distance thresholds used: these are often arbitrary, based on administrative boundaries or constrained by definitions available in the dataset. This causes problems with comparison across studies, and in some cases where migration distance is poorly defined could lead to issues with interpretation of results. Using Binary Logistic Regression and drawing on data from the 2011 Census Sample of Anonymised Records for England and Wales, we demonstrate that the odds of migrating vary when considering a range of population characteristics across 16 distance thresholds. We argue that the choice of distance cut‐offs needs to be population and context specific and that decisions about these cut‐offs should be made carefully as part of the study design