Background: Socioeconomic status and ethnicity are not incorporated as predictors in country-level cardiovascular risk charts on mainland Europe. The aim of this study was to quantify the sex-specific cardiovascular death rates stratified by ethnicity and socioeconomic factors in an urban population in a universal healthcare system. Methods: Age-standardized death rates (ASDR) were estimated in a dynamic population, aged 45À75 in the city of The Hague, the Netherlands, over the period 2007À2018, using data of Statistics Netherlands. Results were stratified by sex, ethnicity (country of birth) and socioeconomic status (prosperity) and compared with a European cut-off for high-risk countries (ASDR men 225/100,000 and women 175/100,000). Findings: In total, 3073 CVD deaths occurred during 1¢76 million person years follow-up. Estimated ASDRs (selected countries of birth) ranged from 126 (95%CI 89À174) in Moroccan men to 379 (95%CI 272À518) in Antillean men, and from 86 (95%CI 50À138) in Moroccan women to 170 (95%CI 142À202) in Surinamese women. ASDRs in the highest and lowest prosperity quintiles were 94 (95%CI 90À98) and 343 (95%CI 334À351) for men, and 43 (95%CI 41À46) and 140 (95%CI 135À145), for women, respectively. Interpretation: In a diverse urban population, large health disparities in cardiovascular ASDRs exists across ethnic and socioeconomic subgroups. Identifying these high-risk subgroups followed by targeted preventive efforts, might provide a basis for improving cardiovascular health equity within communities. Instead of classifying countries as high-risk or low-risk, a shift towards focusing on these subgroups within countries might be needed.

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Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): Leiden University Medical Centre University Leiden. Background/introduction There is much evidence on cardiovascular health disparities in different ethnic and socioeconomic subgroups in (European) populations. Whether ethnicity and socioeconomic status should explicitly be taken into account as predictors in European risk prediction models, on top of traditional risk factors (blood pressure, cholesterol, age and gender), is still considered as a gap in evidence by the 2021 ESC Guideline on cardiovascular disease prevention. Purpose To assess the performance of the cardiovascular SCORE2 risk prediction model in ethnic and socioeconomic subgroups. Methods External validation of the SCORE2 risk model in a population-based study stratified by ethnicity (country of origin), and socioeconomic status (disposable household income). Results In total 6966 cardiovascular disease (CVD) events were observed versus 5495 events predicted by the SCORE2 model. Relative underprediction was the same in men and women (observed/mean predicted (OE-ratio) 1.3 and 1.2 in men and women, respectively). Underprediction was largest in the Surinamese subgroup (OE-ratio 1.9, in both men and women), particularly in the low socioeconomic Surinamese subgroups (OE-ratio 2,5 and 2.1 in men and women, respectively). In Dutch and the combined "other ethnicities", underprediction was observed in low socioeconomic subgroups too: OE-ratio 1.5 and 1.7 in men and women, respectively. Discrimination showed moderate performance in all subgroups, with C-statistics between 0.65 and 0.72, which is similar to discrimination of the SCORE2 model in the development study. Conclusions The SCORE 2 CVD risk model for low-risk countries (as the Netherlands are) was found to under predict CVD risk, particularly in low socioeconomic and Surinamese ethnic subgroups. Taking both socioeconomic status and ethnicity into account as predictors in CVD risk models is desirable for adequate CVD risk prediction and counselling.

Background:Female-specific factors and psychosocial factors may be important in the prediction of stroke, but are not included in prediction models that are currently used. We investigated whether addition of these factors would improve the performance of prediction models for the risk of stroke in women under 50.Patients & methods:We used data from the STIZON, population-based, primary care database of women aged 20–49 years without a history of cardiovascular disease. Analyses were stratified by 10-year age intervals at cohort entry. Cox proportional hazards models to predict stroke risk were developed, including traditional cardiovascular factors, and compared with models that additionally included female-specific and psychosocial factors. We compared the risk models using the C-statistic and the slope of the calibration curve at a follow-up of 10 years. We developed an age-specific stroke risk prediction tool that may help communicating the risk of stroke in clinical practice.Results:We included 409,026 women with a total of 3,990,185 person years of follow-up. Stroke occurred in 2,751 women (incidence rate 6.9 [95%CI:6.6–7.2] per 10,000 person years). Models with only traditional cardiovascular factors performed poorly to moderately in all age groups: 20–29 years: C-statistic: 0.617 (95%CI:0.592–0.639); 30–39 years: C-statistic: 0.615 (95%CI:0.596–0.634); 40–49 years: C-statistic: 0.585 (95%CI:0.573–0.597). After adding the female-specific and psychosocial risk factors to the reference models, the model discrimination increased moderately, especially in the age groups 30–39 (ΔC-statistic: 0.019) and 40–49 years (ΔC-statistic: 0.029) compared to the reference models, respectively.Conclusion:The addition of female-specific factors and psychosocial risk factors improves the discriminatory performance of prediction models for stroke in women under 50.