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Impact of socioeconomic deprivation on screening for cardiovascular disease risk in a primary prevention population: a cross-sectional study.

ABSTRACT: Investigate the association between socioeconomic deprivation and completeness of cardiovascular disease (CVD) risk factor recording in primary care, uptake of screening in people with incomplete risk factor recording and with actual CVD risk within the screened subgroup.Cross-sectional study.Nine UK general practices.7987 people aged 50-74 years with no CVD diagnosis.CVD risk was estimated using the Framingham equation from data extracted from primary care electronic health records. Where there was insufficient information to calculate risk, patients were invited to attend a screening assessment.Proportion of patients for whom clinical data were sufficiently complete to enable CVD risk to be calculated; proportion of patients invited to screening who attended; proportion of patients who attended screening whose 10-year risk of a cardiovascular event was high (>20%). For each outcome, a set of logistic regression models were run. Crude and adjusted ORs were estimated for person-level deprivation, age, gender and smoking status. We included practice-level deprivation as a continuous variable and practice as a random effect to account for clustering.People who had lower Indices of Multiple Deprivation (IMD) scores (less deprived) had significantly worse routine CVD risk factor recording (adjusted OR 0.97 (0.95 to 1.00) per IMD decile; p=0.042). Screening attendance was poorer in those with more deprivation (adjusted OR 0.89 (0.86 to 0.91) per IMD decile; p<0.001). Among those who attended screening, the most deprived were more likely to have CVD risk >20% (OR 1.09 (1.03 to 1.15) per IMD decile; p=0.004).Our data suggest that those who had the most to gain from screening were least likely to attend, potentially exacerbating existing health inequalities. Future research should focus on tailoring the delivery of CVD screening to ensure engagement of socioeconomically deprived groups.

SUBMITTER: Lang SJ

PROVIDER: S-EPMC4809080 | biostudies-other | 2016 Mar

REPOSITORIES: biostudies-other

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Project description:BackgroundSocioeconomic deprivation is associated with higher cardiovascular morbidity and mortality. Whether deprivation status should be incorporated in more cardiovascular risk estimation scores remains unclear. This study evaluates how socioeconomic deprivation status affects the performance of 3 primary prevention cardiovascular risk scores.MethodsThe Generation Scotland Scottish Family Health Study was used to evaluate the performance of 3 cardiovascular risk scores with (ASSIGN [Assessing cardiovascular risk using SIGN (Scottish Intercollegiate Guidelines Network) guidelines to ASSIGN preventive treatment]) and without (SCORE2 [Systematic Coronary Risk Evaluation 2 algorithm], Pooled Cohort Equations) socioeconomic deprivation as a covariate in the risk prediction model. Deprivation was defined by Scottish Index of Multiple Deprivation score. The predicted 10-year risk was evaluated against the observed event rate for the cardiovascular outcome of each risk score. The comparison was made across 3 groups defined by the deprivation index score consisting of group 1 defined as most deprived, group 3 defined as least deprived, and group 2, which consisted of individuals in the middle deprivation categories.ResultsThe study population consisted of 15 506 individuals (60.0% female, median age of 51). Across the population, 1808 (12%) individuals were assigned to group 1 (most deprived), 8119 (52%) to group 2, and 4708 (30%) to group 3 (least deprived), and 871 (6%) individuals had a missing deprivation score. Risk scores based on models that did not include deprivation status significantly under predicted risk in the most deprived (6.43% observed versus 4.63% predicted for SCORE2 [P=0.001] and 6.69% observed versus 4.66% predicted for Pooled Cohort Equations [P<0.001]). Both risk scores also significantly overpredicted the risk in the least deprived group (3.97% observed versus 4.72% predicted for SCORE2 [P=0.007] and 4.22% observed versus 4.85% predicted for Pooled Cohort Equations [P=0.028]). In contrast, no significant difference was demonstrated in the observed versus predicted risk when using the ASSIGN risk score, which included socioeconomic deprivation status in the risk model.ConclusionsSocioeconomic status is a largely unrecognized risk factor in primary prevention of cardiovascular disease. Risk scores that exclude socioeconomic deprivation as a covariate under- and overestimate the risk in the most and least deprived individuals, respectively. This study highlights the importance of incorporating socioeconomic deprivation status in risk estimation systems to ultimately reduce inequalities in health care provision for cardiovascular disease.

Project description:BackgroundStatins are an important intervention for primary and secondary cardiovascular disease (CVD) prevention. We aimed to establish the variation in primary preventive treatment for CVD with statins in the English population.MethodsCross sectional analyses of 6155 English primary care practices with 40,017,963 patients in 2006/7. Linear regression was used to model prescribing rates of statins for primary CVD prevention as a function of IMD (index of multiple deprivation) quintile, proportion of population from an ethnic minority, and age over 65 years. Defined Daily Doses (DDD) were used to calculate the numbers of patients receiving a statin. Statin prescriptions were allocated to primary and secondary prevention based on the prevalence of CVD and stroke.ResultsWe estimated that 10.5% (s.d.3.7%) of the registered population were dispensed a statin for any indication and that 6.3% (s.d. 3.0%) received a statin for primary CVD prevention. The regression model explained 21.2% of the variation in estimates of prescribing for primary prevention. Practices with higher prevalence of hypertension (β co-efficient 0.299 p <0.001) and diabetes (β co-efficient 0.566 p < 0.001) prescribed more statins for primary prevention. Practices with higher levels of ethnicity (β co-efficient-0.026 p <0.001), greater deprivation (β co-efficient -0.152 p < 0.001) older patients (β co-efficient -0.032 p 0.002), larger lists (β co-efficient -0.085, p < 0.001) and were more rural (β co-efficient -0.121, p0.026) prescribed fewer statins. In a small proportion of practices (0.5%) estimated prescribing rates for statins were so low that insufficient prescriptions were issued to meet the predicted secondary prevention requirements of their registered population.ConclusionsAbsolute estimated prescribing rates for primary prevention of CVD were 6.3% of the population. There was evidence of social inequalities in statin prescribing for primary prevention. These findings support the recent introduction of a financial incentive for primary prevention of CVD in England.

Project description:Primary care providers play an important role in preventing and managing cardiovascular disease. This study compared the quality of preventive cardiovascular care delivery amongst different primary care models.This is a secondary analysis of a larger randomized control trial, known as the Improved Delivery of Cardiovascular Care (IDOCC) through Outreach Facilitation. Using baseline data collected through IDOCC, we conducted a cross-sectional study of 82 primary care practices from three delivery models in Eastern Ontario, Canada: 43 fee-for-service, 27 blended-capitation and 12 community health centres with salary-based physicians. Medical chart audits from 4,808 patients with or at high risk of developing cardiovascular disease were used to examine each practice's adherence to ten evidence-based processes of care for diabetes, chronic kidney disease, dyslipidemia, hypertension, weight management, and smoking cessation care. Generalized estimating equation models adjusting for age, sex, rurality, number of cardiovascular-related comorbidities, and year of data collection were used to compare guideline adherence amongst the three models.The percentage of patients with diabetes that received two hemoglobin A1c tests during the study year was significantly higher in community health centres (69%) than in fee-for-service (45%) practices (Adjusted Odds Ratio (AOR) = 2.4 [95% CI 1.4-4.2], p = 0.001). Blended capitation practices had a significantly higher percentage of patients who had their waistlines monitored than in fee-for-service practices (19% vs. 5%, AOR = 3.7 [1.8-7.8], p = 0.0006), and who were recommended a smoking cessation drug when compared to community health centres (33% vs. 16%, AOR = 2.4 [1.3-4.6], p = 0.007). Overall, quality of diabetes care was higher in community health centres, while smoking cessation care and weight management was higher in the blended-capitation models. Fee-for-service practices had the greatest gaps in care, most noticeably in diabetes care and weight management.This study adds to the evidence suggesting that primary care delivery model impacts quality of care. These findings support current Ontario reforms to move away from the traditional fee-for-service practice.ClinicalTrials.gov: NCT00574808.

Project description:OBJECTIVES:The National Mental Health Survey (NMHS) of India was undertaken with the objectives of (1) estimating the prevalence and patterns of various mental disorders in representative Indian population and (2) identifying the treatment gap, healthcare utilisation, disabilities and impact of mental disorders. This paper highlights findings pertaining to depressive disorders (DD) from the NMHS. DESIGN:Multisite population-based cross-sectional study. Subjects were selected by multistage stratified random cluster sampling technique with random selection based on probability proportionate to size at each stage. SETTING:Conducted across 12 states in India (representing varied cultural and geographical diversity), employing uniform, standardised and robust methodology. PARTICIPANTS:A total of 34 802 adults (>18 years) were interviewed. MAIN OUTCOME MEASURE:Prevalence of depressive disorders (ICD-10 DCR) diagnosed using Mini International Neuropsychiatric Interview V.6.0. RESULTS:The weighted prevalence of lifetime and current DD was 5.25% (95% CI: 5.21% to 5.29%, n=34 802) and 2.68% (95% CI: 2.65% to 2.71%, n=34 802), respectively. Prevalence was highest in the 40-59 age groups (3.6%, n=10 302), among females (3.0%, n=18 217) and those residing in cities with population >1 million (5.2%, n=4244). Age, gender, place of residence, education and household income were found to be significantly associated with current DD. Nearly two-thirds of individuals with DD reported disability of varying severity, and the treatment gap for depression in the study population was 79.1%. On an average, households spent INR1500/month (~US$ 23.0/month) towards care of persons affected with DD. CONCLUSION:Around 23 million adults would need care for DD in India at any given time. Since productive population is affected most, DD entails considerable socioeconomic impact at individual and family levels. This is a clarion call for all the concerned stakeholders to scale up services under National Mental Health Programme in India along with integrating care for DD with other ongoing national health programmes.

Project description:People who experience psychological distress have an elevated risk of incident cardiovascular disease (CVD). However, the extent to which traditional CVD prevention strategies could be used to reduce the CVD burden in this group is unclear because population-level data on CVD risk profiles and appropriate management of risk in relation to distress are currently not available. The aim of this study was to use nationally representative data to quantify variation in CVD risk and appropriate management of risk according to level of psychological distress in the Australian population. Data were from 2,618 participants aged 45-74 years without prior CVD who participated in the 2011-12 Australian Health Survey, a cross-sectional and nationally representative study of Australian adults. Age-and sex-adjusted prevalence of 5-year absolute risk of primary CVD (low <10%, moderate 10-15%, or high >15%), CVD risk factors, blood-pressure, and cholesterol assessments, and appropriate treatment (combined blood pressure- and lipid-lowering medication) if at high primary risk, were estimated. Prevalence ratios (PR) quantified variation in these outcomes in relation to low (Kessler-10 score: 10-<12), mild (12-<16), moderate (16-<22) and high (22-50) psychological distress, after adjusting for sociodemographic characteristics. The prevalence of high absolute risk of primary CVD for low, mild, moderate and high distress was 10.9, 12.3, 11.4, and 18.6%, respectively, and was significantly higher among participants with high compared to low distress (adjusted PR:1.62, 95%CI:1.04-2.52). The prevalence of CVD risk factors was generally higher in those with higher psychological distress. Blood pressure and cholesterol assessments were reported by the majority of participants (>85%) but treatment of high absolute risk was low (<30%), and neither were related to psychological distress. Our findings confirm the importance of recognizing people who experience psychological distress as a high risk group and suggest that at least part of the excess burden of primary CVD events among people with high psychological distress could be reduced with an absolute risk approach to assessment and improved management of high primary CVD risk.

Project description:BackgroundBenefit-targeted statin prescribing may be superior to risk-targeted statin prescribing (the current standard), but the impact and efficiency of this approach are unclear.Methods and resultsWe analyzed the National Health and Nutrition Examination Survey (NHANES) using an open-source model (the Prevention Impact and Efficiency Model) to compare targeting of statin therapy according to expected benefit (benefit-targeted) versus baseline risk (risk-targeted) in terms of projected population-level impact and efficiency. Impact was defined as relative % reduction in atherosclerotic cardiovascular disease in the US population for the given strategy compared to current statin treatment patterns; and efficiency as the number needed to treat over 10 years (NNT10, average and maximum) to prevent each atherosclerotic cardiovascular disease event. Benefit-targeted moderate-intensity statin therapy at a treatment threshold of 2.3% expected 10-year absolute risk reduction could produce a 5.7% impact (95% confidence interval, 4.8-6.7). This is approximately equivalent to the potential impact of risk-targeted therapy at a treatment threshold of 5% 10-year atherosclerotic cardiovascular disease risk (5.6% impact [4.7-6.6]). Whereas the estimated maximum NNT10 is much improved for benefit-targeted versus risk-targeted therapy at these equivalent-impact thresholds (43.5 vs 180), the average NNT10 is nearly equivalent (24.2 vs 24.6). Reaching 10% impact (half the Healthy People 2020 impact objective, loosely defined) is theoretically possible with benefit-targeted moderate-intensity statins of persons with expected absolute risk reduction >2.3% if we expand age eligibility and account for treatment of all persons with diabetes mellitus or with low-density lipoprotein >190 mg/dL (impact=12.4%; average NNT10=23.0).ConclusionsBenefit-based targeting of statin therapy provides modest gains in efficiency over risk-based prescribing and could theoretically help attain approximately half of the Healthy People 2020 impact goal with reasonable efficiency.

Project description:Background Statins are a first line, evidence-based yet underprescribed treatment for cardiovascular primary prevention. In primary care settings, multimorbidity is a complex situation which makes it difficult to apply prevention guidelines. Aim To assess the associations between multimorbidity and prescription of statins in accordance with the 2016 ESC recommendations (“appropriate prescription”), and to identify the factors and conditions associated with these prescriptions. Design and setting Cross-sectional prospective study in the French region of Rhône-Alpes among 40 general practitioners and their patients. Methods We examined the association between appropriate statin prescription and several patient characteristics, including multimorbidity, using multivariate logistic regression models. Results Between August 2017 and February 2019, 327 patients were included in the study. Seventy-four (22.6%) were on statin medication and 199 (60.9%) exhibited multimorbidity, defined as ≥2 diseases. Only 22.5% of eligible patients were prescribed statins for primary prevention. Diabetes was most strongly associated with appropriate statin prescription (aOR 8.10, CI 95: 3.81–17.80). Multimorbidity was not associated with appropriate statin prescription (aOR 1.31, CI 95: 0.54–3.26), except in the presence of diabetes which defined diabetic multimorbidity (aOR 10.46, CI 95: 4.87–23.35). Conversely, non-diabetic multimorbidity was associated with lower odds of being appropriately prescribed a statin (aOR 0.26, CI 95: 0.12–0.56). Conclusion Multimorbidity, in itself, does not seem to be a determinant factor for appropriate statin prescription. The latter appears to be determined by a patient’s type of multimorbidity, especially the presence or not of diabetes. Differentiating between diabetic and non-diabetic multimorbidity may be a pragmatic way for GPs to improve primary prevention in a patient-centered and shared decision-making approach.

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Impact of socioeconomic deprivation on screening for cardiovascular disease risk in a primary prevention population: a cross-sectional study.

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