Frailty in COPD: an analysis of prevalence and clinical impact using UK Biobank.

BACKGROUND: Frailty, a state of reduced physiological reserve, is common in people with chronic obstructive pulmonary disease (COPD). Frailty can occur at any age; however, the implications in younger people (eg, aged <65 years) with COPD are unclear. We assessed the prevalence of frailty in UK Biobank participants with COPD; explored relationships between frailty and forced expiratory volume in 1 second (FEV1) and quantified the association between frailty and adverse outcomes. METHODS: UK Biobank participants (n=3132, recruited 2006-2010) with COPD aged 40-70 years were analysed comparing two frailty measures (frailty phenotype and frailty index) at baseline. Relationship with FEV1 was assessed for each measure. Outcomes were mortality, major adverse cardiovascular event (MACE), all-cause hospitalisation, hospitalisation with COPD exacerbation and community COPD exacerbation over 8 years of follow-up. RESULTS: Frailty was common by both definitions (17% frail using frailty phenotype, 28% moderate and 4% severely frail using frailty index). The frailty phenotype, but not the frailty index, was associated with lower FEV1. Frailty phenotype (frail vs robust) was associated with mortality (HR 2.33; 95% CI 1.84 to 2.96), MACE (2.73; 1.66 to 4.49), hospitalisation (incidence rate ratio 3.39; 2.77 to 4.14) hospitalised exacerbation (5.19; 3.80 to 7.09) and community exacerbation (2.15; 1.81 to 2.54), as was frailty index (severe vs robust) (mortality (2.65; 95% CI 1.75 to 4.02), MACE (6.76; 2.68 to 17.04), hospitalisation (3.69; 2.52 to 5.42), hospitalised exacerbation (4.26; 2.37 to 7.68) and community exacerbation (2.39; 1.74 to 3.28)). These relationships were similar before and after adjustment for FEV1. CONCLUSION: Frailty, regardless of age or measure, identifies people with COPD at risk of adverse clinical outcomes. Frailty assessment may aid risk stratification and guide-targeted intervention in COPD and should not be limited to people aged >65 years.

Beyond 10-Year Risk: A Cost-Effectiveness Analysis of Statins for the Primary Prevention of Cardiovascular Disease.

BACKGROUND: Cholesterol guidelines typically prioritize primary prevention statin therapy on the basis of 10-year risk of cardiovascular disease. The advent of generic pricing may justify expansion of statin eligibility. Moreover, 10-year risk may not be the optimal approach for statin prioritization. We estimated the cost-effectiveness of expanding preventive statin eligibility and evaluated novel approaches to prioritization from a Scottish health sector perspective. METHODS: A computer simulation model predicted long-term health and cost outcomes in Scottish adults ≥40 years of age. Epidemiologic analysis was completed using the Scottish Heart Health Extended Cohort, Scottish Morbidity Records, and National Records of Scotland. A simulation cohort was constructed with data from the Scottish Health Survey 2011 and contemporary population estimates. Treatment and cost inputs were derived from published literature and health service cost data. The main outcome measure was the lifetime incremental cost-effectiveness ratio, evaluated as cost (2020 GBP) per quality-adjusted life-year (QALY) gained. Three approaches to statin prioritization were analyzed: 10-year risk scoring using the ASSIGN score, age-stratified risk thresholds to increase treatment rates in younger individuals, and absolute risk reduction (ARR)-guided therapy to increase treatment rates in individuals with elevated cholesterol levels. For each approach, 2 policies were considered: treating the same number of individuals as those with an ASSIGN score ≥20% (age-stratified risk threshold 20, ARR 20) and treating the same number of individuals as those with an ASSIGN score ≥10% (age-stratified risk threshold 10, ARR 10). RESULTS: Compared with an ASSIGN score ≥20%, reducing the risk threshold for statin initiation to 10% expanded eligibility from 804 000 (32% of adults ≥40 years of age without CVD) to 1 445 500 individuals (58%). This policy would be cost-effective (incremental cost-effectiveness ratio, £12 300/QALY [95% CI, £7690/QALY-£26 500/QALY]). Incremental to an ASSIGN score ≥20%, ARR 20 produced ≈8800 QALYs and was cost-effective (£7050/QALY [95% CI, £4560/QALY-£10 700/QALY]). Incremental to an ASSIGN score ≥10%, ARR 10 produced ≈7950 QALYs and was cost-effective (£11 700/QALY [95% CI, £9250/QALY-£16 900/QALY]). Both age-stratified risk threshold strategies were dominated (ie, more expensive and less effective than alternative treatment strategies). CONCLUSIONS: Generic pricing has rendered preventive statin therapy cost-effective for many adults. ARR-guided therapy is more effective than 10-year risk scoring and is cost-effective.

A comparison of routine and case-managed pathways for recovery from musculoskeletal disorders in people in employment.

PURPOSE: To compare outcomes in employed people from an enhanced routine management pathway for musculoskeletal disorders within National Health Service Scotland with an existing active case-management system, Working Health Services Scotland. MATERIALS AND METHODS: The study comprised a service evaluation using anonymised routinely collected data from all currently employed callers presenting with musculoskeletal disorder to the two services. Baseline demographic and clinical data were collected. EuroQol EQ-5DTM scores at the start and end of treatment were compared for both groups, overall and by age, sex, socio-economic status, and anatomical site, and the impact of mental health status at baseline was evaluated. RESULTS: Active case-management resulted in greater improvement than enhanced routine care. Case-managed service users entered the programme earlier in the recovery pathway; there was evidence of spontaneous improvement during the longer waiting time of routine service clients but only if they had good baseline mental health. Those most disadvantaged through mental health co-morbidity showed the greatest benefit. CONCLUSIONS: People with musculoskeletal disorders who have poor baseline mental health status derive greatest benefit from active case-management. Case-management therefore contributes to reducing health inequalities and can help to minimise long-term sickness absence. Shorter waiting times contributed to better outcomes in the case-managed service. Implications for RehabilitationMusculoskeletal disorders are a major cause of inability to work.Case-management is effective in helping people with musculoskeletal disorders to return to work.People who have the poorest mental health are likely to gain the greatest benefit from case-management of their musculoskeletal disorders.

Lipoprotein(a) and cardiovascular disease: prediction, attributable risk fraction, and estimating benefits from novel interventions.

AIMS: To investigate the population attributable fraction due to elevated lipoprotein (a) (Lp(a)) and the utility of measuring Lp(a) in cardiovascular disease (CVD) risk prediction. METHODS AND RESULTS: In 413 734 participants from UK Biobank, associations of serum Lp(a) with composite fatal/non-fatal CVD (n = 10 066 events), fatal CVD (n = 3247), coronary heart disease (CHD; n = 18 292), peripheral vascular disease (PVD; n = 2716), and aortic stenosis (n = 901) were compared using Cox models. Median Lp(a) was 19.7 nmol/L (interquartile interval 7.6-75.3 nmol/L). About 20.8% had Lp(a) values >100 nmol/L; 9.2% had values >175 nmol/L. After adjustment for classical risk factors, 1 SD increment in log Lp(a) was associated with a hazard ratio for fatal/non-fatal CVD of 1.12 [95% confidence interval (CI) 1.10-1.15]. Similar associations were observed with fatal CVD, CHD, PVD, and aortic stenosis. Adding Lp(a) to a prediction model containing traditional CVD risk factors in a primary prevention group improved the C-index by +0.0017 (95% CI 0.0008-0.0026). In the whole cohort, Lp(a) above 100 nmol/L was associated with a population attributable fraction (PAF) of 5.8% (95% CI 4.9-6.7%), and for Lp(a) above 175 nmol/L the PAF was 3.0% (2.4-3.6%). Assuming causality and an achieved Lp(a) reduction of 80%, an ongoing trial to lower Lp(a) in patients with CVD and Lp(a) above 175 nmol/L may reduce CVD risk by 20.0% and CHD by 24.4%. Similar benefits were also modelled in the whole cohort, regardless of baseline CVD. CONCLUSION: Population screening for elevated Lp(a) may help to predict CVD and target Lp(a) lowering drugs, if such drugs prove efficacious, to those with markedly elevated levels.

Changes over 15 years in the contribution of adiposity and smoking to deaths in England and Scotland.

BACKGROUND: For many years smoking has been the major threat to public health in developed countries. However, smoking prevalence has declined over a period when adiposity has increased. The aim of this study was to determine whether adiposity now accounts for more deaths than smoking in the general population as a whole or sub-groups of it. METHODS: This is a comparative risk assessment study using Health Surveys for England and Scottish Health Surveys from 2003 to 2017. Annual prevalence of overweight, obesity, current and former smoking were obtained and combined using population-based weights. Sex-specific risk ratios for all-cause mortality were obtained from the most recently published meta-analyses. Population attributable fractions across yeas were then estimated. FINDINGS: Overall, deaths attributable to current/former smoking declined from 23.1% (95% CI 20.6-25.8%) in 2003 to 19.4% (95% CI 17.3-21.6%) in 2017, whilst those attributable to adiposity (overweight or obesity) increased from 17.9% (95% CI 17.3-18.4%) in 2003 to 23.1% (95% CI 22.3-23.8%) in 2017 with cross-over occurring in 2013. Cross-over occurred earlier in men (2011) than women (2014). It occurred in 2006 for those aged over 65 years of age and in 2012 for those aged 45-64 years. Below 45 years, smoking remained the larger contributor to mortality. INTERPRETATION: Adiposity now accounts for more deaths in England and Scotland than smoking among people in middle- and old-age. National strategies to address adiposity should be a public health priority.

Real-World Estimates of Adrenal Insufficiency-Related Adverse Events in Children With Congenital Adrenal Hyperplasia.

BACKGROUND: Although congenital adrenal hyperplasia (CAH) is known to be associated with adrenal crises (AC), its association with patient- or clinician-reported sick day episodes (SDE) is less clear. METHODS: Data on children with classic 21-hydroxylase deficiency CAH from 34 centers in 18 countries, of which 7 were Low or Middle Income Countries (LMIC) and 11 were High Income (HIC), were collected from the International CAH Registry and analyzed to examine the clinical factors associated with SDE and AC. RESULTS: A total of 518 children-with a median of 11 children (range 1, 53) per center-had 5388 visits evaluated over a total of 2300 patient-years. The median number of AC and SDE per patient-year per center was 0 (0, 3) and 0.4 (0.0, 13.3), respectively. Of the 1544 SDE, an AC was reported in 62 (4%), with no fatalities. Infectious illness was the most frequent precipitating event, reported in 1105 (72%) and 29 (47%) of SDE and AC, respectively. On comparing cases from LMIC and HIC, the median SDE per patient-year was 0.75 (0, 13.3) vs 0.11 (0, 12.0) (P < 0.001), respectively, and the median AC per patient-year was 0 (0, 2.2) vs 0 (0, 3.0) (P = 0.43), respectively. CONCLUSIONS: The real-world data that are collected within the I-CAH Registry show wide variability in the reported occurrence of adrenal insufficiency-related adverse events. As these data become increasingly used as a clinical benchmark in CAH care, there is a need for further research to improve and standardize the definition of SDE.

Risk assessments and structured care interventions for prevention of foot ulceration in diabetes: development and validation of a prognostic model.

BACKGROUND: Diabetes-related foot ulcers give rise to considerable morbidity, generate a high monetary cost for health and social care services and precede the majority of diabetes-related lower extremity amputations. There are many clinical prediction rules in existence to assess risk of foot ulceration but few have been subject to validation. OBJECTIVES: Our objectives were to produce an evidence-based clinical pathway for risk assessment and management of the foot in people with diabetes mellitus to estimate cost-effective monitoring intervals and to perform cost-effectiveness analyses and a value-of-information analysis. DESIGN: We developed and validated a prognostic model using predictive modelling, calibration and discrimination techniques. An overview of systematic reviews already completed was followed by a review of randomised controlled trials of interventions to prevent foot ulceration in diabetes mellitus. A review of the health economic literature was followed by the construction of an economic model, an analysis of the transitional probability of moving from one foot risk state to another, an assessment of cost-effectiveness and a value-of-information analysis. INTERVENTIONS: The effects of simple and complex interventions and different monitoring intervals for the clinical prediction rules were evaluated. MAIN OUTCOME MEASURE: The main outcome was the incidence of foot ulceration. We compared the new clinical prediction rules in conjunction with the most effective preventative interventions at different monitoring intervals with a 'treat-all' strategy. DATA SOURCES: Data from an electronic health record for 26,154 people with diabetes mellitus in one Scottish health board were used to estimate the monitoring interval. The Prediction Of Diabetic foot UlcerationS (PODUS) data set was used to develop and validate the clinical prediction rule. REVIEW METHODS: We searched for eligible randomised controlled trials of interventions using search strategies created for Ovid® (Wolters Kluwer, Alphen aan den Rijn, the Netherlands), MEDLINE, EMBASE and the Cochrane Central Register of Controlled Trials. Randomised controlled trials in progress were identified via the International Standard Randomised Controlled Trial Number Registry and systematic reviews were identified via PROSPERO. Databases were searched from inception to February 2019. RESULTS: The clinical prediction rule was found to accurately assess the risk of foot ulceration. Digital infrared thermometry, complex interventions and therapeutic footwear with offloading devices were found to be effective in preventing foot ulcers. The risk of developing a foot ulcer did not change over time for most people. We found that interventions to prevent foot ulceration may be cost-effective but there is uncertainty about this. Digital infrared thermometry and therapeutic footwear with offloading devices may be cost-effective when used to treat all people with diabetes mellitus regardless of their ulcer risk. LIMITATIONS: The threats to the validity of the results in some randomised controlled trials in the review and the large number of missing data in the electronic health record mean that there is uncertainty in our estimates. CONCLUSIONS: There is evidence that interventions to prevent foot ulceration are effective but it is not clear who would benefit most from receiving the interventions. The ulceration risk does not change over an 8-year period for most people with diabetes mellitus. A change in the monitoring interval from annually to every 2 years for those at low risk would be acceptable. FUTURE WORK RECOMMENDATIONS: Improving the completeness of electronic health records and sharing data would help improve our knowledge about the most clinically effective and cost-effective approaches to prevent foot ulceration in diabetes mellitus. STUDY REGISTRATION: This study is registered as PROSPERO CRD42016052324. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 24, No. 62. See the NIHR Journals Library website for further project information.

People with diabetes sometimes have problems with their feet that can become serious and make getting around harder and life less enjoyable. We have developed a test based on a simple score to find out a person's risk of getting a foot ulcer. We also wanted to know how often the test needs to be done. People who have been tested and learn that they might go on to have foot problems rightly expect to be given treatment that stops the problem happening in the first place. In this project, we read many written reports about the best treatments to prevent foot ulcers. We found that some things can prevent foot ulcers, such as wearing special shoes and insoles, taking the temperature of the skin of the foot and resting when the temperature rises, and receiving specialist care from diabetes foot care teams. However, we also looked at the costs of the test and treatments and found that some treatments are better value for money than others. By using people's health data from NHS computers, we discovered that very few people with diabetes develop a worse risk score for foot ulcers as time goes on, and it seems that being tested every year is not necessary for everyone. New clinical trials might help to improve foot health for people with diabetes, but if all of the researchers who have collected data from people in clinical trials shared their data it would be possible to find out more about who will gain most from these treatments without spending a lot on new research. It is clear that better input of patients' health data into NHS computers will benefit diabetes research in the future.

Author Correction: Glomerular filtration rate by differing measures, albuminuria and prediction of cardiovascular disease, mortality and end-stage kidney disease.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Do age, period or cohort effects explain circulatory disease mortality trends, Scotland 1974-2015?

OBJECTIVE: We aimed to explore whether age, period or cohort effects explain the trends and inequalities in ischaemic heart disease (IHD) and cerebrovascular disease (CeVD) mortality in Scotland. METHODS: We analysed IHD and CeVD deaths for 1974-2015 by sex, age and area deprivation, visually explored the data using heatmaps and dotplots and built regression models. RESULTS: CeVD mortality improved steadily over time while IHD mortality improved more rapidly from the late 1980s. Age effects were evident; both outcomes showed an exponential relationship with age for all except males for IHD in the 1980s and 1990s. The mortality profiles by age became older, although improvement was slower for those aged <50 years for IHD, especially for males, and faster for CeVD in females aged <65 years. Rates were higher, and inequalities greater, among males, especially for IHD. For IHD, increased risk for males over females reduced with age (incidence rate ratio for 41-50 year old males=4.28 (95% CI 4.12 to 4.44) and 1.17 (95% CI 1.16 to 1.18) for 71-80 year olds). Inequalities in IHD mortality by area deprivation persisted over time, increasing from around 10% to around 25% higher risk in the most deprived areas between 1974 and 1986 before declining in absolute terms from around 2000. Inequalities for CeVD increased after the late 1980s. CONCLUSIONS: IHD and CeVD mortality in Scotland exhibit age but not recent distinct period or cohort effects. The improvements in mortality rates have been more sustained for CeVD and inequalities greater for IHD.

Evidence synthesis for constructing directed acyclic graphs (ESC-DAGs): a novel and systematic method for building directed acyclic graphs.

BACKGROUND: Directed acyclic graphs (DAGs) are popular tools for identifying appropriate adjustment strategies for epidemiological analysis. However, a lack of direction on how to build them is problematic. As a solution, we propose using a combination of evidence synthesis strategies and causal inference principles to integrate the DAG-building exercise within the review stages of research projects. We demonstrate this idea by introducing a novel protocol: 'Evidence Synthesis for Constructing Directed Acyclic Graphs' (ESC-DAGs)'. METHODS: ESC-DAGs operates on empirical studies identified by a literature search, ideally a novel systematic review or review of systematic reviews. It involves three key stages: (i) the conclusions of each study are 'mapped' into a DAG; (ii) the causal structures in these DAGs are systematically assessed using several causal inference principles and are corrected accordingly; (iii) the resulting DAGs are then synthesised into one or more 'integrated DAGs'. This demonstration article didactically applies ESC-DAGs to the literature on parental influences on offspring alcohol use during adolescence. CONCLUSIONS: ESC-DAGs is a practical, systematic and transparent approach for developing DAGs from background knowledge. These DAGs can then direct primary data analysis and DAG-based sensitivity analysis. ESC-DAGs has a modular design to allow researchers who are experienced DAG users to both use and improve upon the approach. It is also accessible to researchers with limited experience of DAGs or evidence synthesis.

How did a lower drink-drive limit affect bar trade and drinking practices? A qualitative study of how alcohol retailers experienced a change in policy.

INTRODUCTION AND AIMS: Reducing the legal drink-drive limit from 0.08% to 0.05% blood alcohol concentration (BAC) can reduce road traffic accidents and deaths if properly enforced. Reduced limits may be opposed by alcohol retail and manufacturing industries on the basis of commercial impact. Our aim was to qualitatively explore how a reduction in the drink-drive limit from 0.08% to 0.05% BAC in Scotland, was experienced by bar owners or managers, including any resultant changes in customer drinking or business practice. This is the first study of this type. DESIGN AND METHODS: Semi-structured interviews were conducted with 16 owners and managers of on-trade premises in Scotland in 2018, approximately three years after the drink-drive limit was reduced. Data were analysed using thematic analysis. RESULTS: Most participants reported no long-term financial impact on their business, but a few, mainly from rural areas, reported some reduction in alcohol sales. Observed drinking changes included fewer people drinking after work or leaving premises earlier on weekdays. Adaptations to businesses included improving the range of no/low-alcohol drinks and food offered. Changes such as these were seen as key to minimising economic impact. DISCUSSION AND CONCLUSIONS: Opposition to legislative measures that impact on commercial interests is often strong and receives significant public attention. This study found that Scottish businesses that adapted to the drink-drive limit change reported little long-term economic impact. These findings are of international relevance as potential BAC limit reductions in several other jurisdictions remain the subject of debate, including regarding the impact on business.

Glycated Hemoglobin, Prediabetes, and the Links to Cardiovascular Disease: Data From UK Biobank.

OBJECTIVE: HbA1c levels are increasingly measured in screening for diabetes; we investigated whether HbA1c may simultaneously improve cardiovascular disease (CVD) risk assessment, using QRISK3, American College of Cardiology/American Heart Association (ACC/AHA), and Systematic COronary Risk Evaluation (SCORE) scoring systems. RESEARCH DESIGN AND METHODS: UK Biobank participants without baseline CVD or known diabetes (n = 357,833) were included. Associations of HbA1c with CVD was assessed using Cox models adjusting for classical risk factors. Predictive utility was determined by the C-index and net reclassification index (NRI). A separate analysis was conducted in 16,596 participants with known baseline diabetes. RESULTS: Incident fatal or nonfatal CVD, as defined in the QRISK3 prediction model, occurred in 12,877 participants over 8.9 years. Of participants, 3.3% (n = 11,665) had prediabetes (42.0-47.9 mmol/mol [6.0-6.4%]) and 0.7% (n = 2,573) had undiagnosed diabetes (≥48.0 mmol/mol [≥6.5%]). In unadjusted models, compared with the reference group (<42.0 mmol/mol [<6.0%]), those with prediabetes and undiagnosed diabetes were at higher CVD risk: hazard ratio (HR) 1.83 (95% CI 1.69-1.97) and 2.26 (95% CI 1.96-2.60), respectively. After adjustment for classical risk factors, these attenuated to HR 1.11 (95% CI 1.03-1.20) and 1.20 (1.04-1.38), respectively. Adding HbA1c to the QRISK3 CVD risk prediction model (C-index 0.7392) yielded a small improvement in discrimination (C-index increase of 0.0004 [95% CI 0.0001-0.0007]). The NRI showed no improvement. Results were similar for models based on the ACC/AHA and SCORE risk models. CONCLUSIONS: The near twofold higher unadjusted risk for CVD in people with prediabetes is driven mainly by abnormal levels of conventional CVD risk factors. While HbA1c adds minimally to cardiovascular risk prediction, those with prediabetes should have their conventional cardiovascular risk factors appropriately measured and managed.

Glomerular filtration rate by differing measures, albuminuria and prediction of cardiovascular disease, mortality and end-stage kidney disease.

Chronic kidney disease is common in the general population and associated with excess cardiovascular disease (CVD), but kidney function does not feature in current CVD risk-prediction models. We tested three formulae for estimated glomerular filtration rate (eGFR) to determine which was the most clinically informative for predicting CVD and mortality. Using data from 440,526 participants from UK Biobank, eGFR was calculated using serum creatinine, cystatin C (eGFRcys) and creatinine-cystatin C. Associations of each eGFR with CVD outcome and mortality were compared using Cox models and adjusting for atherosclerotic risk factors (per relevant risk scores), and the predictive utility was determined by the C-statistic and categorical net reclassification index. We show that eGFRcys is most strongly associated with CVD and mortality, and, along with albuminuria, adds predictive discrimination to current CVD risk scores, whilst traditional creatinine-based measures are weakly associated with risk. Clinicians should consider measuring eGFRcys as part of cardiovascular risk assessment.

What causes the burden of stroke in Scotland? A comparative risk assessment approach linking the Scottish Health Survey to administrative health data.

BACKGROUND: The availability of robust evidence to inform effective public health decision making is becoming increasingly important, particularly in a time of competing health demands and limited resources. Comparative Risk Assessments (CRA) are useful in this regard as they quantify the contribution of modifiable exposures to the disease burden in a population. The aim of this study is to assess the contribution of a range of modifiable exposures to the burden of disease due to stroke, an important public health problem in Scotland. METHODS: We used individual-level response data from eight waves (1995-2012) of the Scottish Health Survey linked to acute hospital discharge records from the Scottish Morbidity Record 01 (SMR01) and cause of death records from the death register. Stroke was defined using the International Classification of Disease (ICD) 9 codes 430-431, 433-4 and 436; and the ICD10 codes I60-61 and I63-64 and stroke incidence was defined as a composite of an individual's first hospitalisation or death from stroke. A literature review identified exposures causally linked to stroke. Exposures were mapped to the layers of the Dahlgren & Whitehead model of the determinants of health and Population Attributable Fractions were calculated for each exposure deemed a significant causal risk of stroke from a Cox Proportional Hazards Regression model. Population Attributable Fractions were not summed as they may add to more than 100% due to the possibility of a person being exposed to more than one exposure simultaneously. RESULTS: Overall, the results suggest that socioeconomic factors explain the largest proportion of incident stroke hospitalisations and deaths, after adjustment for confounding. After DAG adjustment, low education explained 38.8% (95% Confidence Interval 26.0% to 49.4%, area deprivation (as measured by the Scottish Index of Multiple Deprivation) 34.9% (95% CI 26.4 to 42.4%), occupational social class differences 30.3% (95% CI 19.4% to 39.8%), high systolic blood pressure 29.6% (95% CI 20.6% to 37.6%), smoking 25.6% (95% CI 17.9% to 32.6%) and area deprivation (as measured by the Carstairs area deprivation Index) 23.5% (95% CI 14.4% to 31.7%), of incident strokes in Scotland after adjustment. CONCLUSION: This study provides evidence for prioritising interventions that tackle socioeconomic inequalities as a means of achieving the greatest reduction in avoidable strokes in Scotland. Future work to disentangle the proportion of the effect of deprivation transmitted through intermediate mediators on the pathway between socioeconomic inequalities and stroke may offer additional opportunities to reduce the incidence of stroke in Scotland.

Comparison of Conventional Lipoprotein Tests and Apolipoproteins in the Prediction of Cardiovascular Disease.

BACKGROUND: Total cholesterol and high-density lipoprotein cholesterol (HDL-C) measurements are central to cardiovascular disease (CVD) risk assessment, but there is continuing debate around the utility of other lipids for risk prediction. METHODS: Participants from UK Biobank without baseline CVD and not taking statins, with relevant lipid measurements (n=346 686), were included in the primary analysis. An incident fatal or nonfatal CVD event occurred in 6216 participants (1656 fatal) over a median of 8.9 years. Associations of nonfasting lipid measurements (total cholesterol, HDL-C, non-HDL-C, direct and calculated low-density lipoprotein cholesterol [LDL-C], and apolipoproteins [Apo] A1 and B) with CVD were compared using Cox models adjusting for classical risk factors, and predictive utility was determined by the C-index and net reclassification index. Prediction was also tested in 68 649 participants taking a statin with or without baseline CVD (3515 CVD events). RESULTS: ApoB, LDL-C, and non-HDL-C were highly correlated (r>0.90), while HDL-C was strongly correlated with ApoA1 (r=0.92). After adjustment for classical risk factors, 1 SD increase in ApoB, direct LDL-C, and non-HDL-C had similar associations with composite fatal/nonfatal CVD events (hazard ratio, 1.23, 1.20, 1.21, respectively). Associations for 1 SD increase in HDL-C and ApoA1 were also similar (hazard ratios, 0.81 [both]). Adding either total cholesterol and HDL-C, or ApoB and ApoA, to a CVD risk prediction model (C-index, 0.7378) yielded similar improvement in discrimination (C-index change, 0.0084; 95% CI, 0.0065, 0.0104, and 0.0089; 95% CI, 0.0069, 0.0109, respectively). Once total and HDL-C were in the model, no further substantive improvement was achieved with the addition of ApoB (C-index change, 0.0004; 95% CI, 0.0000, 0.0008) or any measure of LDL-C. Results for predictive utility were similar for a fatal CVD outcome, and in a discordance analysis. In participants taking a statin, classical risk factors (C-index, 0.7118) were improved by non-HDL-C (C-index change, 0.0030; 95% CI, 0.0012, 0.0048) or ApoB (C-index change, 0.0030; 95% CI, 0.0011, 0.0048). However, adding ApoB or LDL-C to a model already containing non-HDL-C did not further improve discrimination. CONCLUSIONS: Measurement of total cholesterol and HDL-C in the nonfasted state is sufficient to capture the lipid-associated risk in CVD prediction, with no meaningful improvement from addition of apolipoproteins, direct or calculated LDL-C.

Brazilian Analytical Decision Model for Cardiovascular Disease: An Adaptation of the Scottish Cardiovascular Disease Policy Model.

INTRODUCTION: Despite the significant impact of cardiovascular disease (CVD), there is not yet an analytical decision tool for assessing efficiency of interventions to prevent primary CVD events in Brazil. Therefore, we sought to adapt a Scottish CVD Policy Model to be used in the proposed population. METHODS: Calibration consisted of identifying multiplicative factors for linear predictors of existing survival analysis models to produce predictions that closely match observed data (Life-table and Brazilian cohort study). Target data were life expectancy (LE) and cumulative incidence of coronary heart disease (CHD), cerebrovascular disease (CBVD), fatal CVD and fatal non-CVD. Root-Mean-Square-Error (RMSE) was used to estimate differences between predictions and observations. Acceptance criteria were defined as a fit of less than one year for LE and 1% for cumulative incidence. Male and female models were built separately. RESULTS: The original model underestimated LE (RMSE=2.85 for men and 1.91 for women), CHD and CBVD for women (RMSE=0.044 and 0.041, respectively). The calibration process identified multiplicative factors to reach acceptance criteria for the four target data mentioned above (RMSE=0.61, 0.21, 0.016 and 0.017, respectively). Over prediction was identified only for CHD events in men (RMSE=0.031) being further calibrated (RMSE=0.008). All other target data met the acceptance criteria. Overall, the calibrated model predicts properly to individuals aging 35-80 years old, diabetics or not, smokers or not, with or without family history of CVD, and presenting at least one of the risk factors uncontrolled: Systolic Blood Pressure, Total Cholesterol or HDL-Cholesterol. DISCUSSION: This is the first decision analytic model capable of assessing efficiency of interventions that prevent primary CVD events in Brazil. In future research, independent external validation should be carried out to corroborate the reliability of the model outputs.

Synthetic control methodology as a tool for evaluating population-level health interventions.

BACKGROUND: Many public health interventions cannot be evaluated using randomised controlled trials so they rely on the assessment of observational data. Techniques for evaluating public health interventions using observational data include interrupted time series analysis, panel data regression-based approaches, regression discontinuity and instrumental variable approaches. The inclusion of a counterfactual improves causal inference for approaches based on time series analysis, but the selection of a suitable counterfactual or control area can be problematic. The synthetic control method builds a counterfactual using a weighted combination of potential control units. METHODS: We explain the synthetic control method, summarise its use in health research to date, set out its advantages, assumptions and limitations and describe its implementation through a case study of life expectancy following German reunification. RESULTS: Advantages of the synthetic control method are that it offers an approach suitable when there is a small number of treated units and control units and it does not rely on parallel preimplementation trends like difference in difference methods. The credibility of the result relies on achieving a good preimplementation fit for the outcome of interest between treated unit and synthetic control. If a good preimplementation fit is established over an extended period of time, a discrepancy in the outcome variable following the intervention can be interpreted as an intervention effect. It is critical that the synthetic control is built from a pool of potential controls that are similar to the treated unit. There is currently no consensus on what constitutes a 'good fit' or how to judge similarity. Traditional statistical inference is not appropriate with this approach, although alternatives are available. From our review, we noted that the synthetic control method has been underused in public health. CONCLUSIONS: Synthetic control methods are a valuable addition to the range of approaches for evaluating public health interventions when randomisation is impractical. They deserve to be more widely applied, ideally in combination with other methods so that the dependence of findings on particular assumptions can be assessed.

Association of Total and Differential Leukocyte Counts With Cardiovascular Disease and Mortality in the UK Biobank.

OBJECTIVE: Elevated white blood cell count is associated with a higher risk of cardiovascular disease (CVD). We aimed to investigate whether specific leukocyte subpopulations, which may more closely indicate a specific inflammatory pathway, are specifically associated with CVD. APPROACH AND RESULTS: Participants (478 259) from UK Biobank with data for white blood cell count were included. Death because of CVD (n=1377) and non-CVD causes (n=8987) occurred during median follow-up time of 7.0 years (interquartile range, 6.3-7.6). In Cox models, deciles of leukocyte counts (lymphocytes, monocytes, neutrophils, eosinophils, and basophils) were examined using the fifth decile as the referent group. Models were stratified by sex and adjusted for a range of classical risk factors. A sensitivity analysis excluded participants with baseline comorbidites and the first 2 years of follow-up. Men (hazard ratio [HR], 1.59; 95% confidence interval, 1.22-2.08) and women (HR, 2.15; 95% confidence interval, 1.38-3.35) in the highest decile of neutrophil count were at higher risk of CVD mortality and nonfatal CVD (men HR, 1.28; 95% confidence interval, 1.16-1.42 and women HR, 1.21; 95% confidence interval, 1.06-1.38). In the sensitivity analysis, the power to investigate CVD mortality was limited, but for both sexes combined, the linear HRs for a 1×109/L cell count increase in white blood cell count and neutrophils, respectively, was 1.05 (1.03-1.07) and 1.07 (1.04-1.11). CONCLUSIONS: Among circulating leukocyte subpopulations, neutrophil count in men was most consistently associated with fatal and nonfatal CVD. Further studies of interventions that lower circulating neutrophils, such as canakinumab, are required to investigate causality.

Drug-related deaths in Scotland 1979-2013: evidence of a vulnerable cohort of young men living in deprived areas.

BACKGROUND: Even after accounting for deprivation, mortality rates are higher in Scotland relative to the rest of Western Europe. Higher mortality from alcohol- and drug-related deaths (DRDs), violence and suicide (particularly in young adults) contribute to this 'excess' mortality. Age-period and cohort effects help explain the trends in alcohol-related deaths and suicide, respectively. This study investigated whether age, period or cohort effects might explain recent trends in DRDs in Scotland and relate to exposure to the changing political context from the 1980s. METHODS: We analysed data on DRDs from 1979 to 2013 by sex and deprivation using shaded contour plots and intrinsic estimator regression modelling to identify and quantify relative age, period and cohort effects. RESULTS: The peak age for DRDs fell around 1990, especially for males as rates increased for those aged 18 to 45 years. There was evidence of a cohort effect, especially among males living in the most deprived areas; those born between 1960 and 1980 had an increased risk of DRD, highest for those born 1970 to 1975. The cohort effect started around a decade earlier in the most deprived areas compared to the rest of the population. CONCLUSION: Age-standardised rates for DRDs among young adults rose during the 1990s in Scotland due to an increased risk of DRD for the cohort born between 1960 and 1980, especially for males living in the most deprived areas. This cohort effect is consistent with the hypothesis that exposure to the changing social, economic and political contexts of the 1980s created a delayed negative health impact.