scholarly journals 145Educational inequalities in primary prevention statin use in UK Biobank

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Alice Carter ◽  
Dipender Gill ◽  
Richard Morris ◽  
George Davey Smith ◽  
Amy Taylor ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Cardiovascular Risk ◽  
Educational Attainment ◽  
Self Report ◽  
Risk Scores ◽  
Uk Biobank ◽  
Preventive Medication ◽  
Unit Increase ◽  
Statin Use ◽  
Years Of Schooling

Abstract Background Socioeconomic inequalities in cardiovascular disease are well documented, but the association of socioeconomic position with treatment for cardiovascular disease prevention is unclear. Methods Using data from a large prospective cohort study, UK Biobank, we calculated QRISK3 cardiovascular risk scores for 472 097 eligible participants with complete data on self-reported educational attainment and statin use (55% female; mean age, 56). We used logistic regression to explore the association between i) QRISK3 score and ii) educational attainment on self-report statin use. We then stratified the association between QRISK3 score, and statin use by educational attainment to test for interactions. Results For an equivalent QRISK3 score, more educated individuals were more likely to report taking statins. In women with 7 years of schooling, a one unit increase in QRISK3 score was associated with a 7% higher odds of statin use (odds ratio (OR) 1.07, 95% CI 1.07, 1.07). In women with 20 years of schooling, a one unit increase in QRISK3 score was associated with an 14% higher odds of statin use (OR 1.14, 95% CI 1.14, 1.15). Comparable ORs in men were 1.04 (95% CI 1.04, 1.05) for 7 years of schooling and 1.08 (95% CI 1.08, 1.08) for 20 years of schooling. Conclusions Individuals with less education are less likely to access statins conditional on cardiovascular risk factors. Key messages Inequalities in access to cardiovascular preventive medication are likely contributing to cardiovascular inequalities.

scholarly journals Educational inequalities in statin treatment for preventing cardiovascular disease: cross-sectional analysis of UK Biobank

2020 ◽  
Author(s):  
Alice R Carter ◽  
Dipender Gill ◽  
Richard Morris ◽  
George Davey Smith ◽  
Amy E Taylor ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Primary Care ◽  
Cardiovascular Risk ◽  
Educational Attainment ◽  
Prescription Data ◽  
List Type ◽  
Uk Biobank ◽  
Cross Sectional ◽  
Statin Use ◽  
Years Of Schooling

AbstractImportanceThe most socioeconomically deprived individuals remain at the greatest risk of cardiovascular disease. Differences in risk adjusted use of statins between educational groups may contribute to these inequalities.ObjectiveTo identify whether people with lower levels of educational attainment are less likely to take statins for a given level of cardiovascular risk.DesignCross-sectional analysis of a population-based cohort study and linked longitudinal primary care records.SettingUK Biobank data from baseline assessment centres, linked primary care data and hospital episode statisticsParticipantsUK Biobank participants (N = 489 679, mean age = 56, 54% female) with complete data on educational attainment and self-reported medication use. Secondary analyses were carried out on a subsample of participants with linked primary care data (N = 217 675).Main outcome measuresStatin use self-reported to clinic nurses at baseline assessment centres, validated with linked prescription data in a subsample of participants in secondary analyses.ResultsGreater education was associated with lower statin use, whilst higher cardiovascular risk (assessed by QRISK3 score) was associated with higher statin use in both females and males. There was evidence of an interaction between QRISK3 and education, such that for the same QRISK3 score, people with more education were more likely to report taking statins. For example, in women with 7 years of schooling, equivalent to leaving school with no formal qualifications, a one unit increase in QRISK3 score was associated with a 6% higher odds of statin use (odds ratio (OR) 1.06, 95% CI 1.05, 1.06). In contrast, in women with 20 years of schooling, equivalent to obtaining a degree, a one unit increase in QRISK3 score was associated with an 11% higher odds of statin use (OR 1.11, 95% CI 1.10, 1.11). Comparable ORs in men were 1.04 (95% CI 1.04, 1.05) for men with 7 years of schooling and (95% CI 1.07, 1.07) for men with 20 years of schooling.ConclusionsFor the same level of cardiovascular risk, individuals with lower educational attainment are less likely to receive statins, likely contributing to health inequalities.SummaryWhat is already known on this topic?Despite reductions in the rates of cardiovascular disease in high income countries, individuals who are the most socioeconomically deprived remain at the highest risk.Although intermediate lifestyle and behavioural risk factors explain some of this, much of the effect remains unexplained.What does this study add?For the same increase in QRISK3 score, the likelihood of statin use increased more in individuals with high educational attainment compared with individuals with lower educational attainment.These results were similar when using UK Biobank to derive QRISK3 scores and when using QRISK scores recorded in primary care records, and when using self-reported statin prescription data or prescription data from linked primary care records.The mechanisms leading to these differences are unknown, but both health seeking behaviours and clinical factors may contribute.

scholarly journals Cross-sectional analysis of educational inequalities in primary prevention statin use in UK Biobank

Heart ◽  
2021 ◽  
pp. heartjnl-2021-319238
Author(s):  
Alice Rose Carter ◽  
Dipender Gill ◽  
George Davey Smith ◽  
Amy E Taylor ◽  
Neil M Davies ◽  
...  
Keyword(s):  
Cardiovascular Risk ◽  
Educational Attainment ◽  
Cardiovascular Prevention ◽  
Uk Biobank ◽  
Cross Sectional ◽  
Unit Increase ◽  
Using Data ◽  
Large Prospective Cohort Study ◽  
Statin Use ◽  
Years Of Schooling

ObjectiveIdentify whether participants with lower education are less likely to report taking statins for primary cardiovascular prevention than those with higher education, but an equivalent increase in underlying cardiovascular risk.MethodsUsing data from a large prospective cohort study, UK Biobank, we calculated a QRISK3 cardiovascular risk score for 472 097 eligible participants with complete data on self-reported educational attainment and statin use (55% female participants; mean age 56 years). We used logistic regression to explore the association between (i) QRISK3 score and (ii) educational attainment on self-reported statin use. We then stratified the association between QRISK3 score and statin use, by educational attainment to test for interactions.ResultsThere was evidence of an interaction between QRISK3 score and educational attainment. Per unit increase in QRISK3 score, more educated individuals were more likely to report taking statins. In women with ≤7 years of schooling, a one unit increase in QRISK3 score was associated with a 7% higher odds of statin use (OR 1.07, 95% CI 1.07 to 1.07). In women with ≥20 years of schooling, a one unit increase in QRISK3 score was associated with an 14% higher odds of statin use (OR 1.14, 95% CI 1.14 to 1.15). Comparable ORs in men were 1.04 (95% CI 1.04 to 1.05) for ≤7 years of schooling and 1.08 (95% CI 1.08, 1.08) for ≥20 years of schooling.ConclusionPer unit increase in QRISK3 score, individuals with lower educational attainment were less likely to report using statins, likely contributing to health inequalities.

Advanced cardiometabolic & inflammatory markers for prediction of cardiovascular disease and cancer

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
D Radenkovic ◽  
S.C Chawla ◽  
G Botta ◽  
A Boli ◽  
M.B Banach ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Risk Score ◽  
Cancer Incidence ◽  
Risk Function ◽  
Patient Characteristics ◽  
Risk Scores ◽  
Uk Biobank ◽  
Training Set ◽  
All Cause Mortality ◽  
The Uk

Abstract   The two leading causes of mortality worldwide are cardiovascular disease (CVD) and cancer. The annual total cost of CVD and cancer is an estimated $844.4 billion in the US and is projected to double by 2030. Thus, there has been an increased shift to preventive medicine to improve health outcomes and development of risk scores, which allow early identification of individuals at risk to target personalised interventions and prevent disease. Our aim was to define a Risk Score R(x) which, given the baseline characteristics of a given individual, outputs the relative risk for composite CVD, cancer incidence and all-cause mortality. A non-linear model was used to calculate risk scores based on the participants of the UK Biobank (= 502548). The model used parameters including patient characteristics (age, sex, ethnicity), baseline conditions, lifestyle factors of diet and physical activity, blood pressure, metabolic markers and advanced lipid variables, including ApoA and ApoB and lipoprotein(a), as input. The risk score was defined by normalising the risk function by a fixed value, the average risk of the training set. To fit the non-linear model >400,000 participants were used as training set and >45,000 participants were used as test set for validation. The exponent of risk function was represented as a multilayer neural network. This allowed capturing interdependent behaviour of covariates, training a single model for all outcomes, and preserving heterogeneity of the groups, which is in contrast to CoxPH models which are traditionally used in risk scores and require homogeneous groups. The model was trained over 60 epochs and predictive performance was determined by the C-index with standard errors and confidence intervals estimated with bootstrap sampling. By inputing the variables described, one can obtain personalised hazard ratios for 3 major outcomes of CVD, cancer and all-cause mortality. Therefore, an individual with a risk Score of e.g. 1.5, at any time he/she has 50% more chances than average of experiencing the corresponding event. The proposed model showed the following discrimination, for risk of CVD (C-index = 0.8006), cancer incidence (C-index = 0.6907), and all-cause mortality (C-index = 0.7770) on the validation set. The CVD model is particularly strong (C-index >0.8) and is an improvement on a previous CVD risk prediction model also based on classical risk factors with total cholesterol and HDL-c on the UK Biobank data (C-index = 0.7444) published last year (Welsh et al. 2019). Unlike classically-used CoxPH models, our model considers correlation of variables as shown by the table of the values of correlation in Figure 1. This is an accurate model that is based on the most comprehensive set of patient characteristics and biomarkers, allowing clinicians to identify multiple targets for improvement and practice active preventive cardiology in the era of precision medicine. Figure 1. Correlation of variables in the R(x) Funding Acknowledgement Type of funding source: None

scholarly journals Development and Validation of a Novel Dementia Risk Score in the UK Biobank Cohort

2021 ◽  
Author(s):  
Melis Anatürk ◽  
Raihaan Patel ◽  
Georgios Georgiopoulos ◽  
Danielle Newby ◽  
Anya Topiwala ◽  
...  
Keyword(s):  
At Risk ◽  
Cardiovascular Risk ◽  
Risk Score ◽  
Disease Risk ◽  
Risk Index ◽  
Risk Scores ◽  
Uk Biobank ◽  
Dementia Risk ◽  
History Of ◽  
The Uk

INTRODUCTION: Current prognostic models of dementia have had limited success in consistently identifying at-risk individuals. We aimed to develop and validate a novel dementia risk score (DRS) using the UK Biobank cohort.METHODS: After randomly dividing the sample into a training (n=166,487, 80%) and test set (n=41,621, 20%), logistic LASSO regression and standard logistic regression were used to develop the UKB-DRS.RESULTS: The score consisted of age, sex, education, apolipoprotein E4 genotype, a history of diabetes, stroke, and depression, and a family history of dementia. The UKB-DRS had good-to-strong discrimination accuracy in the UKB hold-out sample (AUC [95%CI]=0.79 [0.77, 0.82]) and in an external dataset (Whitehall II cohort, AUC [95%CI]=0.83 [0.79,0.87]). The UKB-DRS also significantly outperformed four published risk scores (i.e., Australian National University Alzheimer’s Disease Risk Index (ANU-ADRI), Cardiovascular Risk Factors, Aging, and Dementia score (CAIDE), Dementia Risk Score (DRS), and the Framingham Cardiovascular Risk Score (FRS) across both test sets.CONCLUSION: The UKB-DRS represents a novel easy-to-use tool that could be used for routine care or targeted selection of at-risk individuals into clinical trials.

Abstract P160: Is Higher Educational Attainment or Higher Income Protective for Cardiovascular Risk in Deaf American Sign Language (ASL) Users?

Circulation ◽  
2012 ◽  
Vol 125 (suppl_10) ◽  
Author(s):  
Michael M McKee ◽  
Kimberly C McKee ◽  
Erika Sutter ◽  
Thomas Pearson
Keyword(s):  
High School ◽  
Cardiovascular Disease ◽  
Cardiovascular Risk ◽  
General Population ◽  
Educational Attainment ◽  
Sign Language ◽  
Household Income ◽  
Annual Household Income ◽  
Low Education ◽  
Higher Educational Attainment

Background: Deaf ASL users appear to be burdened with higher cardiovascular risk due to communication barriers in the health care setting and from lack of accessible health educational and outreach programs. It is well known among the general population that higher educational attainment and income are highly correlated and provide cardiovascular protection. It is unknown if the same effect is seen among Deaf ASL users. Objective We sought to examine whether educational attainment and/or annual household income are inversely associated with cardiovascular risk in a sample of Deaf ASL users. Methods: The Deaf Health Survey (DHS) is an adapted and translated Behavioral Risk Factor Surveillance System (BRFSS) into sign language. A sample of 339 Deaf adults from the Rochester, New York MSA participated in the 2008 DHS and is included in the analysis. We assessed education (≤high school [low education], some college, and 4 year college degree or higher [referent]) and annual household income (<$25,000 versus ≥$25,000 [referent]). We constructed an aggregate (i.e. self-report of any of the four cardiovascular disease (CVD) equivalents: diabetes, myocardial infarction (MI), cerebral vascular attack (CVA), and angina) and conducted χ² tests of association for education and income. After excluding for any missing data on key variables, we conducted multi-logistic regression adjusting for : age, sex, race/ethnicity, and smoking. Results: In the study sample, 17.6% had ≤ high school education while 36.1% earned <$25,000; income and education were poorly correlated (r= 0.355). Among this sample (mean age= 46.4, range= 18-88), the prevalence of outcomes was: diabetes (9.4%), MI (5.0%), CVA (0.9%), and angina (4.5%). Unadjusted, low education was significantly associated with reporting an aggregate outcome (χ² =15.6; p=0.0004) whereas income was not (χ² =0.79; p=0.37). Low education continued to be significantly associated with increased likelihood of reporting an aggregate outcome (OR 5.057; 95% CI 1.73-14.82) whereas income was not significantly associated with reporting an aggregate outcome (OR 0.91; 95% CI: 0.39-2.12) even after adjustment. Conclusion: This is the first known study documenting that low educational attainment is associated with higher likelihood of reported cardiovascular disease among Deaf individuals. Higher income did not appear to provide a cardiovascular protective effect, unlike in the general population. This may be partially explained by the poor correlation between educational attainment and income in the study sample. Effective and accessible health communication and education with Deaf individuals with lower educational attainment could be addressed by the use of language-concordant providers and interpreters and following principles of clear communication (e.g. teach-back) to address ongoing cardiovascular health disparities.

scholarly journals Baseline 10-Year Cardiovascular Risk Scores Predict Cognitive Function in Older Persons, and Particularly Women, Living With Human Immunodeficiency Virus Infection

2020 ◽  
Author(s):  
Felicia C Chow ◽  
Asya Lyass ◽  
Taylor F Mahoney ◽  
Joseph M Massaro ◽  
Virginia A Triant ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Human Immunodeficiency Virus ◽  
Cardiovascular Risk ◽  
Cognitive Function ◽  
Risk Score ◽  
Risk Scores ◽  
Atherosclerotic Cardiovascular Disease ◽  
Composite Effect ◽  
Immunodeficiency Virus ◽  
Ascvd Risk

Abstract Background Cardiovascular disease (CVD) and associated comorbidities increase the risk of cognitive impairment in persons living with human immunodeficiency virus (PLWH). Given the potential composite effect of multiple cardiovascular risk factors on cognition, we examined the ability of the Atherosclerotic Cardiovascular Disease (ASCVD) risk score and the Framingham Heart Study Global CVD risk score (FRS) to predict future cognitive function in older PLWH. Methods We constructed linear regression models evaluating the association between baseline 10-year cardiovascular risk scores and cognitive function (measured by a summary z-score, the NPZ-4) at a year 4 follow-up visit. Results Among 988 participants (mean age, 52 years; 20% women), mean 10-year ASCVD risk score at entry into the cohort was 6.8% (standard deviation [SD], 7.1%) and FRS was 13.1% (SD, 10.7%). In models adjusted only for cognitive function at entry, the ASCVD risk score significantly predicted year 4 NPZ-4 in the entire cohort and after stratification by sex (for every 1% higher ASCVD risk, year 4 NPZ-4 was lower by 0.84 [SD, 0.28] overall, P = .003; lower by 2.17 [SD, 0.67] in women, P = .001; lower by 0.78 [SD, 0.32] in men, P = .016). A similar relationship was observed between FRS and year 4 NPZ-4. In multivariable models, higher 10-year ASCVD risk and FRS predicted lower NPZ-4 in women. Conclusions Baseline 10-year ASCVD risk and FRS predicted future cognitive function in older PLWH with well-controlled infection. Cardiovascular risk scores may help to identify PLWH, especially women, who are at risk for worse cognition over time.

scholarly journals Acute Myocardial Infarction in a Young Male with Ankylosing Spondylitis – Case Presentation

2020 ◽  
Vol 26 (3) ◽  
pp. 109-112
Author(s):  
Ionescu Mihaela ◽  
Ionescu Paris ◽  
Peniu Luminița ◽  
Șuța Victoria Cristina ◽  
Parepa Irinel-Raluca
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Young Adults ◽  
Cardiovascular Risk ◽  
Ankylosing Spondylitis ◽  
Cardiovascular Risk Factors ◽  
Young Male ◽  
Chronic Inflammatory Disease ◽  
Risk Scores ◽  
Drug Eluting Stent

Abstract Cardiovascular risk scores are useful in early detecting and, most important, early correcting the cardiovascular risk factors in order to prevent the cardiovascular disease, but the most commonly used charts have essential limitations when applied to young adults. We present the case of a 39-year-old man, known with HLA-B27-positive ankylosing spondylitis for 15 years, treated only with nonsteroidal antiinflamatory drugs, without any traditional cardiovascular risk factors, who was diagnosed with severe coronary artery disease, sub-occlusion in the proximal and mid-segment of the left anterior descending artery, which required emergency percutaneous coronary intervention with drug-eluting stent implantation. In this case report we aim to highlight the necessity of considering other parameters such as C-reactive protein levels or carotid plaques when estimating the risk of developing a cardiovascular disease, especially in young adults diagnosed with chronic inflammatory disease.

scholarly journals Accelerometer-derived sleep onset timing and cardiovascular disease incidence: a UK Biobank cohort study

2021 ◽  
Author(s):  
Shahram Nikbakhtian ◽  
Angus B Reed ◽  
Bernard Dillon Obika ◽  
Davide Morelli ◽  
Adam C Cunningham ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Cardiovascular Risk ◽  
Sleep Onset ◽  
Sensitivity Analyses ◽  
Poor Sleep ◽  
Accelerometer Data ◽  
Uk Biobank ◽  
Cvd Risk ◽  
Onset Timing ◽  
Sleep Parameters

Abstract Aims Growing evidence suggests that poor sleep health is associated with cardiovascular risk. However, research in this area often relies upon recollection dependent questionnaires or diaries. Accelerometers provide an alternative tool for measuring sleep parameters objectively. This study examines the association between wrist-worn accelerometer-derived sleep onset timing and cardiovascular disease (CVD). Methods and results We derived sleep onset and waking up time from accelerometer data collected from 103 712 UK Biobank participants over a period of 7 days. From this, we examined the association between sleep onset timing and CVD incidence using a series of Cox proportional hazards models. A total of 3172 cases of CVD were reported during a mean follow-up period of 5.7 (±0.49) years. An age- and sex-controlled base analysis found that sleep onset time of 10:00 p.m.–10:59 p.m. was associated with the lowest CVD incidence. An additional model, controlling for sleep duration, sleep irregularity, and established CVD risk factors, did not attenuate this association, producing hazard ratios of 1.24 (95% confidence interval, 1.10–1.39; P &lt; 0.005), 1.12 (1.01–1.25; P= 0.04), and 1.25 (1.02–1.52; P= 0.03) for sleep onset &lt;10:00 p.m., 11:00 p.m.–11:59 p.m., and ≥12:00 a.m., respectively, compared to 10:00 p.m.–10:59 p.m. Importantly, sensitivity analyses revealed this association with increased CVD risk was stronger in females, with only sleep onset &lt;10:00 p.m. significant for males. Conclusions Our findings suggest the possibility of a relationship between sleep onset timing and risk of developing CVD, particularly for women. We also demonstrate the potential utility of collecting information about sleep parameters via accelerometry-capable wearable devices, which may serve as novel cardiovascular risk indicators.

scholarly journals Associations Between Systolic Interarm Differences in Blood Pressure and Cardiovascular Disease Outcomes and Mortality

Hypertension ◽  
2020 ◽  
Author(s):  
Christopher E. Clark ◽  
Fiona C. Warren ◽  
Kate Boddy ◽  
Sinead T.J. McDonagh ◽  
Sarah F. Moore ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Cardiovascular Disease ◽  
Cardiovascular Risk ◽  
Cardiovascular Events ◽  
Hazard Ratio ◽  
Risk Scores ◽  
Individual Participant Data ◽  
Hazard Ratios ◽  
All Cause Mortality ◽  
Individual Participant

Systolic interarm differences in blood pressure have been associated with all-cause mortality and cardiovascular disease. We undertook individual participant data meta-analyses to (1) quantify independent associations of systolic interarm difference with mortality and cardiovascular events; (2) develop and validate prognostic models incorporating interarm difference, and (3) determine whether interarm difference remains associated with risk after adjustment for common cardiovascular risk scores. We searched for studies recording bilateral blood pressure and outcomes, established agreements with collaborating authors, and created a single international dataset: the Inter-arm Blood Pressure Difference - Individual Participant Data (INTERPRESS-IPD) Collaboration. Data were merged from 24 studies (53 827 participants). Systolic interarm difference was associated with all-cause and cardiovascular mortality: continuous hazard ratios 1.05 (95% CI, 1.02–1.08) and 1.06 (95% CI, 1.02–1.11), respectively, per 5 mm Hg systolic interarm difference. Hazard ratios for all-cause mortality increased with interarm difference magnitude from a ≥5 mm Hg threshold (hazard ratio, 1.07 [95% CI, 1.01–1.14]). Systolic interarm differences per 5 mm Hg were associated with cardiovascular events in people without preexisting disease, after adjustment for Atherosclerotic Cardiovascular Disease (hazard ratio, 1.04 [95% CI, 1.00–1.08]), Framingham (hazard ratio, 1.04 [95% CI, 1.01–1.08]), or QRISK cardiovascular disease risk algorithm version 2 (QRISK2) (hazard ratio, 1.12 [95% CI, 1.06–1.18]) cardiovascular risk scores. Our findings confirm that systolic interarm difference is associated with increased all-cause mortality, cardiovascular mortality, and cardiovascular events. Blood pressure should be measured in both arms during cardiovascular assessment. A systolic interarm difference of 10 mm Hg is proposed as the upper limit of normal. REGISTRATION: URL: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42015031227

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