COVID-19 risk mitigation in reopening mass cultural events: population-based observational study for the UK Events Research Programme in Liverpool City Region.

OBJECTIVES: To understand severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission risks, perceived risks and the feasibility of risk mitigations from experimental mass cultural events before coronavirus disease 2019 (COVID-19) restrictions were lifted. DESIGN: Prospective, population-wide observational study. SETTING: Four events (two nightclubs, an outdoor music festival and a business conference) open to Liverpool City Region UK residents, requiring a negative lateral flow test (LFT) within the 36 h before the event, but not requiring social distancing or face-coverings. PARTICIPANTS: A total of 12,256 individuals attending one or more events between 28 April and 2 May 2021. MAIN OUTCOME MEASURES: SARS-CoV-2 infections detected using audience self-swabbed (5-7 days post-event) polymerase chain reaction (PCR) tests, with viral genomic analysis of cases, plus linked National Health Service COVID-19 testing data. Audience experiences were gathered via questionnaires, focus groups and social media. Indoor CO2 concentrations were monitored. RESULTS: A total of 12 PCR-positive cases (likely 4 index, 8 primary or secondary), 10 from the nightclubs. Two further cases had positive LFTs but no PCR. A total of 11,896 (97.1%) participants with scanned tickets were matched to a negative pre-event LFT: 4972 (40.6%) returned a PCR within a week. CO2 concentrations showed areas for improving ventilation at the nightclubs. Population infection rates were low, yet with a concurrent outbreak of >50 linked cases around a local swimming pool without equivalent risk mitigations. Audience anxiety was low and enjoyment high. CONCLUSIONS: We observed minor SARS-CoV-2 transmission and low perceived risks around events when prevalence was low and risk mitigations prominent. Partnership between audiences, event organisers and public health services, supported by information systems with real-time linked data, can improve health security for mass cultural events.

Evaluating the impact of using mobile vaccination units to increase COVID-19 vaccination uptake in Cheshire and Merseyside, UK: a synthetic control analysis.

OBJECTIVE: To evaluate the impact of mobile vaccination units on COVID-19 vaccine uptake of the first dose, the percentage of vaccinated people among the total eligible population. We further investigate whether such an effect differed by deprivation, ethnicity and age. DESIGN: Synthetic control analysis. SETTING: The population registered with general practices (GPs) in nine local authority areas in Cheshire and Merseyside in Northwest England, UK. INTERVENTION: Mobile vaccination units that visited 37 sites on 54 occasions between 12 April 2021 and 28 June 2021. We defined intervention neighbourhoods as having their population weighted centroid located within 1 km of mobile vaccination sites (338 006 individuals). A weighted combination of neighbourhoods that had not received the intervention (1 495 582 individuals) was used to construct a synthetic control group. OUTCOME: The weekly number of first-dose vaccines received among people aged 18 years and over as a proportion of the population. RESULTS: The introduction of a mobile vaccination unit into a neighbourhood increased the number of first vaccinations conducted in the neighbourhood by 25% (95% CI 21% to 28%) within 3 weeks after the first visit to a neighbourhood, compared with the synthetic control group. Interaction analyses showed smaller or no effect among older age groups, Asian and black ethnic groups, and the most socioeconomically deprived populations. CONCLUSIONS: Mobile vaccination units are effective interventions for increasing vaccination uptake, at least in the short term. While mobile units can be geographically targeted to reduce inequalities, we found evidence that they may increase inequalities in vaccine uptake within targeted areas, as the intervention was less effective among groups that tended to have lower vaccination uptake. Mobile vaccination units should be used in combination with activities to maximise outreach with black and Asian communities and socioeconomically disadvantaged groups.

Evaluating social and spatial inequalities of large scale rapid lateral flow SARS-CoV-2 antigen testing in COVID-19 management: An observational study of Liverpool, UK (November 2020 to January 2021).

BACKGROUND: Large-scale asymptomatic testing of communities in Liverpool (UK) for SARS-CoV-2 was used as a public health tool for containing COVID-19. The aim of the study is to explore social and spatial inequalities in uptake and case-detection of rapid lateral flow SARS-CoV-2 antigen tests (LFTs) offered to people without symptoms of COVID-19. METHODS: Linked pseudonymised records for asymptomatic residents in Liverpool who received a LFT for COVID-19 between 6th November 2020 to 31st January 2021 were accessed using the Combined Intelligence for Population Health Action resource. Bayesian Hierarchical Poisson Besag, York, and Mollié models were used to estimate ecological associations for uptake and positivity of testing. FINDINGS: 214 525 residents (43%) received a LFT identifying 5192 individuals as positive cases of COVID-19 (1.3% of tests were positive). Uptake was highest in November when there was military assistance. High uptake was observed again in the week preceding Christmas and was sustained into a national lockdown. Overall uptake were lower among males (e.g. 40% uptake over the whole period), Black Asian and other Minority Ethnic groups (e.g. 27% uptake for 'Mixed' ethnicity) and in the most deprived areas (e.g. 32% uptake in most deprived areas). These population groups were also more likely to have received positive tests for COVID-19. Models demonstrated that uptake and repeat testing were lower in areas of higher deprivation, areas located further from test sites and areas containing populations less confident in the using Internet technologies. Positive tests were spatially clustered in deprived areas. INTERPRETATION: Large-scale voluntary asymptomatic community testing saw social, ethnic, digital and spatial inequalities in uptake. COVID-19 testing and support to isolate need to be more accessible to the vulnerable communities most impacted by the pandemic, including non-digital means of access. FUNDING: Department of Health and Social Care (UK) and Economic and Social Research Council.

Assessing life-space mobility for a more holistic view on wellbeing in geriatric research and clinical practice.

Life-space mobility (LSM) is a holistic measure of resilience to physical decline and social isolation in later life. To promote its use as an outcome in geriatric studies and in clinical practice, this review paper explains the concept of LSM; outlines available questionnaires for LSM assessment, provides an overview of associations between LSM and other outcomes, and discusses emerging methods to measure LSM using wearable sensors. Based on performed activity around a central geographical anchor, LSM aims to quantify the observed contraction of daily activities associated with ageing. Several questionnaires are available to assess LSM in different contexts: the University of Alabama Life-Space Assessment and the Life-Space Questionnaire (community settings), the Nursing Home Life-Space Diameter (nursing home settings) and Life Space at Home (for house-bound populations). Some studies using GPS trackers to calculate life-space parameters reported promising results. Although these techniques reduce data collection burden, battery life and older people's willingness to wear a tracker require further improvement before they can be used more widely. Regardless of the assessment method used, LSM was associated with measures of functional and cognitive abilities, nursing home admission and mortality. The current availability of instruments, the ongoing development of less burdensome data collection techniques, and evidence of construct validity support a case for promoting integration of LSM assessments into geriatric research studies and clinical practice. Ultimately, this will provide a more holistic view on older people's health and wellbeing.

Lung function trajectories from pre-school age to adulthood and their associations with early life factors: a retrospective analysis of three population-based birth cohort studies.

BACKGROUND: Maximal lung function in early adulthood is an important determinant of mortality and COPD. We investigated whether distinct trajectories of lung function are present during childhood and whether these extend to adulthood and infancy. METHODS: To ascertain trajectories of FEV1, we studied two population-based birth cohorts (MAAS and ALSPAC) with repeat spirometry from childhood into early adulthood (1046 participants from 5-16 years and 1390 participants from 8-24 years). We used a third cohort (PIAF) with repeat lung function measures in infancy (V'maxFRC) and childhood (FEV1; 196 participants from 1 month to 18 years of age) to investigate whether these childhood trajectories extend from early life. We identified trajectories using latent profile modelling. We created an allele score to investigate genetic associations of trajectories, and constructed a multivariable model to identify their early-life predictors. FINDINGS: We identified four childhood FEV1 trajectories: persistently high, normal, below average, and persistently low. The persistently low trajectory (129 [5%] of 2436 participants) was associated with persistent wheezing and asthma throughout follow-up. In genetic analysis, compared with the normal trajectory, the pooled relative risk ratio per allele was 0·96 (95% CI 0·92-1·01; p=0·13) for persistently high, 1·01 (0·99-1·02; p=0·49) for below average, and 1·05 (0·98-1·13; p=0·13) for persistently low. Most children in the low V'maxFRC trajectory in infancy did not progress to the low FEV1 trajectory in childhood. Early-life factors associated with the persistently low trajectory included recurrent wheeze with severe wheezing exacerbations, early allergic sensitisation, and tobacco smoke exposure. INTERPRETATION: Reduction of childhood smoke exposure and minimisation of the risk of early-life sensitisation and wheezing exacerbations might reduce the risk of diminished lung function in early adulthood. FUNDING: None.

The influence of patient portals on users' decision making is insufficiently investigated: A systematic methodological review.

BACKGROUND: Patient portals are considered valuable conduits for supporting patients' self-management. However, it is unknown why they often fail to impact on health care processes and outcomes. This may be due to a scarcity of robust studies focusing on the steps that are required to induce improvement: users need to effectively interact with the portal (step 1) in order to receive information (step 2), which might influence their decision-making (step 3). We aimed to explore this potential knowledge gap by investigating to what extent each step has been investigated for patient portals, and explore the methodological approaches used. METHODS: We performed a systematic literature review using Coiera's information value chain as a guiding theoretical framework. We searched MEDLINE and Scopus by combining terms related to patient portals and evaluation methodologies. Two reviewers selected relevant papers through duplicate screening, and one extracted data from the included papers. RESULTS: We included 115 articles. The large majority (n = 104) evaluated aspects related to interaction with patient portals (step 1). Usage was most often assessed (n = 61), mainly by analysing system interaction data (n = 50), with most authors considering participants as active users if they logged in at least once. Overall usability (n = 57) was commonly assessed through non-validated questionnaires (n = 44). Step 2 (information received) was investigated in 58 studies, primarily by analysing interaction data to evaluate usage of specific system functionalities (n = 34). Eleven studies explicitly assessed the influence of patient portals on patients' and clinicians' decisions (step 3). CONCLUSIONS: Whereas interaction with patient portals has been extensively studied, their influence on users' decision-making remains under-investigated. Methodological approaches to evaluating usage and usability of portals showed room for improvement. To unlock the potential of patient portals, more (robust) research should focus on better understanding the complex process of how portals lead to improved health and care.

Investigating heterogeneity of effects and associations using interaction terms.

Effect heterogeneity, the variability of an association or exposure across subgroups, usually warrants further investigation. The aim of this deeper analysis is to identify effect modifiers (or moderators) and quantify their relationship with the exposure. We explain why it is better to harness interaction effects within a single analytic model than to use separate models to analyze each subgroup. Using examples, we demonstrate a practical approach to modeling and interpretation with interaction terms from various measurement scales (categorical by categorical; categorical by continuous; and continuous by continuous).

Geographical epidemiology of health and overall deprivation in England, its changes and persistence from 2004 to 2015: a longitudinal spatial population study.

BACKGROUND: Socioeconomic deprivation is a key determinant for health. In England, the Index of Multiple Deprivation (IMD) is a widely used composite measure of deprivation. However, little is known about its spatial clustering or persistence across time. METHODS: Data for overall IMD and its health domain were analysed for 2004-2015 at a low geographical area (average of 1500 people). Levels and temporal changes were spatially visualised for the whole of England and its 10 administrative regions. Spatial clustering was quantified using Moran's I, correlations over time were quantified using Pearson's r. RESULTS: Between 2004 and 2015 we observed a strong persistence for both overall (r=0.94) and health-related deprivation (r=0.92). At the regional level, small changes were observed over time, but with areas slowly regressing towards the mean. However, for the North East, North West and Yorkshire, where health-related deprivation was the highest, the decreasing trend in health-related deprivation reversed and we noticed increases in 2015. Results did not support our hypothesis of increasing spatial clustering over time. However, marked regional variability was observed in both aggregate deprivation outcomes. The lowest autocorrelation was seen in the North East and changed very little over time, while the South East had the highest autocorrelation at all time points. CONCLUSIONS: Overall and health-related deprivation patterns persisted in England, with large and unchanging health inequalities between the North and the South. The spatial aspect of deprivation can inform the targeting of health and social care interventions, particularly in areas with high levels of deprivation clustering.

North-South disparities in English mortality1965-2015: longitudinal population study.

BACKGROUND: Social, economic and health disparities between northern and southern England have persisted despite Government policies to reduce them. We examine long-term trends in premature mortality in northern and southern England across age groups, and whether mortality patterns changed after the 2008-2009 Great Recession. METHODS: Population-wide longitudinal (1965-2015) study of mortality in England's five northernmost versus four southernmost Government Office Regions - halves of overall population. MAIN OUTCOME MEASURE: directly age-sex adjusted mortality rates; northern excess mortality (percentage excess northern vs southern deaths, age-sex adjusted). RESULTS: From 1965 to 2010, premature mortality (deaths per 10 000 aged <75 years) declined from 64 to 28 in southern versus 72 to 35 in northern England. From 2010 to 2015 the rate of decline in premature mortality plateaued in northern and southern England. For most age groups, northern excess mortality remained consistent from 1965 to 2015. For 25-34 and 35-44 age groups, however, northern excess mortality increased sharply between 1995 and 2015: from 2.2% (95% CI -3.2% to 7.6%) to 29.3% (95% CI 21.0% to 37.6%); and 3.3% (95% CI -1.0% to 7.6%) to 49.4% (95% CI 42.8% to 55.9%), respectively. This was due to northern mortality increasing (ages 25-34) or plateauing (ages 35-44) from the mid-1990s while southern mortality mainly declined. CONCLUSIONS: England's northern excess mortality has been consistent among those aged <25 and 45+ for the past five decades but risen alarmingly among those aged 25-44 since the mid-90s, long before the Great Recession. This profound and worsening structural inequality requires more equitable economic, social and health policies, including potential reactions to the England-wide loss of improvement in premature mortality.

Obesity paradox and mortality in adults with and without incident type 2 diabetes: a matched population-level cohort study.

OBJECTIVE: Among adults with type 2 diabetes (T2D), several (but not all) studies show that being overweight (body mass index (BMI): 25.0-29.9 kg/m2) or obese I (BMI: 30.0-34.9 kg/m2) near the time of diagnosis, is unexpectedly associated with reduced all-cause mortality compared with normal weight-the obesity paradox. We addressed whether this observation is causal (eg, a true protective effect); due to confounding (including effect modification); or due to selection ('collider') bias. RESEARCH DESIGN AND METHODS: We performed a matched population-level cohort study using primary care records from Salford, UK (1995-2012) in 10 464 patients with incident T2D paired (1:3) with 31 020 individuals who never developed T2D. We estimated HRs for associations of BMI with all-cause mortality using Cox models, stratified by smoking status. RESULTS: Median follow-up was 8.7 years. For never smokers, the hazard of all-cause mortality increased from 25 kg/m2, in a linear manner, with increasing BMI in the T2D cohort (HR per 5 kg/m2: 1.23, ptrend<0.001) and in the non-diabetes cohort (HR per 5 kg/m2: 1.34, ptrend<0.001). In contrast, among ever smokers, BMI-mortality relationships were U-shaped in the T2D and non-diabetes cohorts. Evidence of the obesity paradox in ever smokers, with and without T2D, argued against a selection bias, but supported a contribution of effect modification by smoking (pinteraction=0.009). Results were stable to various sensitivity analyses. CONCLUSIONS: In this cohort, the obesity paradox is mainly explained by smoking as an effect modifier. These findings indicate that the obesity paradox does not challenge standard weight management recommendations among T2D patients.

Patient Portal Adoption Rates: A Systematic Literature Review and Meta-Analysis.

Despite the increasing availability of online patient portals that provide access to electronic health records, little is known about their adoption by patients. We systematically reviewed the literature to investigate adoption of patient portals across studies. We searched MEDLINE and Scopus to identify relevant papers. We included 40 studies: 24 were controlled experiments, with prospective data collection in an actively recruited population; 16 were real-world experiments, with adoption being evaluated retrospectively after system deployment in clinical practice. Our meta-analysis showed an overall mean adoption rate of 52% (95% Confidence Interval [CI], 42 to 62%). Rates differed markedly between study types: controlled experiments yielded a mean adoption rate of 71% (95% CI 64 to 79%), compared to 23% (95% CI, 13 to 33%) in real-world experiments. This difference was confirmed in a meta-regression analysis of the influence of study characteristics on adoption rates. Our findings suggest that adoption rates reported in controlled studies do not reflect those in everyday clinical practice. Until we understand how to effectively increase adoption, patient portals are unlikely to consistently lead to improvements in care processes and health outcomes.

Predicting mortality from change-over-time in the Charlson Comorbidity Index: A retrospective cohort study in a data-intensive UK health system.

Multimorbidity is common among older people and presents a major challenge to health systems worldwide. Metrics of multimorbidity are, however, crude: focusing on measuring comorbid conditions at single time-points rather than reflecting the longitudinal and additive nature of chronic conditions. In this paper, we explore longitudinal comorbidity metrics and their value in predicting mortality.Using linked primary and secondary care data, we conducted a retrospective cohort study on adults in Salford, UK from 2005 to 2014 (n = 287,459). We measured multimorbidity with the Charlson Comorbidity Index (CCI) and quantified its changes in various time windows. We used survival models to assess the relationship between CCI changes and mortality, controlling for gender, age, baseline CCI, and time-dependent CCI. Goodness-of-fit was assessed with the Akaike Information Criterion and discrimination with the c-statistic.Overall, 15.9% patients experienced a change in CCI after 10 years, with a mortality rate of 19.8%. The model that included gender and time-dependent age, CCI, and CCI change across consecutive time windows had the best fit to the data but equivalent discrimination to the other time-dependent models. The absolute CCI score gave a constant hazard ratio (HR) of around 1.3 per unit increase, while CCI change afforded greater prognostic impact, particularly when it occurred in shorter time windows (maximum HR value for the 3-month time window, with 1.63 and 95% confidence interval 1.59-1.66).Change over time in comorbidity is an important but overlooked predictor of mortality, which should be considered in research and care quality management.

A contemporary risk model for predicting 30-day mortality following percutaneous coronary intervention in England and Wales.

BACKGROUND: The current risk model for percutaneous coronary intervention (PCI) in the UK is based on outcomes of patients treated in a different era of interventional cardiology. This study aimed to create a new model, based on a contemporary cohort of PCI treated patients, which would: predict 30 day mortality; provide good discrimination; and be well calibrated across a broad risk-spectrum. METHODS AND RESULTS: The model was derived from a training dataset of 336,433 PCI cases carried out between 2007 and 2011 in England and Wales, with 30 day mortality provided by record linkage. Candidate variables were selected on the basis of clinical consensus and data quality. Procedures in 2012 were used to perform temporal validation of the model. The strongest predictors of 30-day mortality were: cardiogenic shock; dialysis; and the indication for PCI and the degree of urgency with which it was performed. The model had an area under the receiver operator characteristic curve of 0.85 on the training data and 0.86 on validation. Calibration plots indicated a good model fit on development which was maintained on validation. CONCLUSION: We have created a contemporary model for PCI that encompasses a range of clinical risk, from stable elective PCI to emergency primary PCI and cardiogenic shock. The model is easy to apply and based on data reported in national registries. It has a high degree of discrimination and is well calibrated across the risk spectrum. The examination of key outcomes in PCI audit can be improved with this risk-adjusted model.

Body mass index relates weight to height differently in women and older adults: serial cross-sectional surveys in England (1992-2011).

BACKGROUND: Body mass index (BMI) tends to be higher among shorter adults, especially women. The dependence of BMI-height correlation on age and calendar time may inform us about temporal determinants of BMI. METHODS: Series of cross-sectional surveys: Health Survey for England, 1992-2011. We study the Benn Index, which is the coefficient in a regression of log(weight) on log(height). This is adjusted for age, gender and calendar time, allowing for non-linear terms and interactions. RESULTS: By height quartile, mean BMI decreased with increasing height, more so in women than in men (P < 0.001). The decrease in mean BMI in the tallest compared with the shortest height quartile was 0.77 in men (95% CI 0.69, 0.86) and 1.98 in women (95% CI 1.89, 2.08). Regression analysis of log(weight) on log(height) revealed that the inverse association between BMI and height was more pronounced in older adults and stronger in women than in men, with little change over calendar time. CONCLUSIONS: Unlike early childhood, where taller children tend to have higher BMI, adults, especially women and older people, show an inverse BMI-height association. BMI is a heterogeneous measure of weight-for-height; height may be an important and complex determinant of BMI trajectory over the life course.

Predicting heart failure decompensation using cardiac implantable electronic devices: a review of practices and challenges.

Cardiac implantable electronic devices include remote monitoring tools intended to guide heart failure management. The monitoring focus has been on averting hospitalizations by predicting worsening heart failure. However, although device measurements including intrathoracic impedance correlate with risk of decompensation, they individually predict hospitalizations with limited accuracy. Current 'crisis detection' methods involve repeatedly screening for impending decompensation, and do not adhere to the principles of diagnostic testing. Complex substrate, limited test performance, low outcome incidence, and long test to outcome times inevitably generate low positive and high negative predictive values. When combined with spectrum bias, the generalizability, incremental value, and cost-effectiveness of device algorithms are questionable. To avoid these pitfalls, remote monitoring may need to shift from crisis detection to health maintenance, keeping the patient within an ideal physiological range through continuous 'closed loop' interaction and dynamic therapy adjustment. Test performance must also improve, possibly through combination with physiological sensors in different dimensions, static baseline characteristics, and biomarkers. Complex modelling may tailor monitoring to individual phenotypes, and thus realize a personalized medicine approach. Future randomized controlled trials should carefully consider these issues, and ensure that the interventions tested are generalizable to clinical practice.

Atopic Dermatitis and Respiratory Allergy: What is the Link.

Understanding the aetiology and progression of atopic dermatitis and respiratory allergy may elucidate early preventative and management strategies aimed towards reducing the global burden of asthma and allergic disease. In this article, we review the current opinion concerning the link between atopic dermatitis and the subsequent progression of respiratory allergies during childhood and into early adolescence. Advances in machine learning and statistical methodology have facilitated the discovery of more refined definitions of phenotypes for identifying biomarkers. Understanding the role of atopic dermatitis in the development of respiratory allergy may ultimately allow us to determine more effective treatment strategies, thus reducing the patient and economic burden associated with these conditions.