Abstract P389: Cardiovascular Disease Mortality Risk Prediction in Educational Classes across European Regions, in the MORGAM Project Populations

Circulation ◽  
2012 ◽  
Vol 125 (suppl_10) ◽  
Author(s):  
Marco M Ferrario ◽  
Giovanni Veronesi ◽  
Lloyd E Chambless ◽  
Hugh Tunstall-Pedoe ◽  
Kari Kuulasmaa ◽  
...  
Keyword(s):  
Risk Factors ◽  
Socioeconomic Status ◽  
High Education ◽  
Risk Prediction ◽  
Central Europe ◽  
East Europe ◽  
Hazard Ratios ◽  
Score Risk ◽  
European Populations ◽  
Cvd Mortality

Aims: Although socioeconomic status is a recognized independent risk factor for CVD mortality, the recommended European risk prediction equation for primary prevention does not consider it; an approach criticized by previous results in the UK and US. We aim to assess whether the SCORE project equation adequately estimates the risk in different educational classes, across several European populations. Methods: We considered 47 prospective population-based surveys from Nordic Countries (Finland, Denmark, Sweden), UK (Belfast and Scotland), Central Europe (France, Germany and Italy) and East Europe (Lithuania, Poland) and Russia. Baseline data collection and mortality follow-up (median time 10 years) adhered to standardized MONICA-like procedures. Three educational classes were derived from population-, sex- and birth year-specific tertiles of years of schooling. The individual SCORE risk was computed from age, total cholesterol, systolic blood pressure and smoking; the risk was recalibrated to the average observed risk in each population. We estimated age- and traditional risk factors-adjusted hazard ratios (HR) for 10 year CVD mortality (highest education as the reference), from Cox models. Moreover, the observed number of fatal CVD events by educational class was compared to the expected number, as estimated by the recalibrated SCORE function. Results: The cohorts summed-up 39,215 men and 29,240 women 40 to 64 years old and free from CVD event at baseline. Education was associated with CVD mortality in men (pooled age-adjusted HR for low vs high education: 1.6, 95% CI 1.4–1.9); the hazard ratios ranged from 1.3 (95%CI: 0.9–1.8) in Central Europe to 2.1 (1.6–2.7) in East Europe and Russia. The association attenuated after adjustment for SCORE risk factors and HDL-cholesterol. Among women, the association was significant in Nordic Countries only (age-adjusted HR for low vas high education: 1.7, 95% CI 1.1–2.6), but it was no more significant after adjustment for multiple risk factors. The original SCORE equation overestimated the risk at a population level, both in men and in women, except in East Europe and Russia. After recalibration, the SCORE equation overestimated the risk among the more educated men by 20% to 50% (in Central Europe, East Europe and Russia, respectively), but underestimated it in the less educated men by 7% to 23% (in Central Europe, East Europe and Russia, respectively). Conclusions: Our results, based on a well-harmonized study comprising several European populations, suggest the need to include country-specific socioeconomic status in the risk estimation equations.

Abstract 17: Association of Race and Sex with Cardiovascular Disease and Non-Cardiovascular Disease Mortality: The REasons for Geographic and Racial Differences in Stroke study

Circulation ◽  
2017 ◽  
Vol 135 (suppl_1) ◽  
Author(s):  
Gabriel S Tajeu ◽  
Monika M Safford ◽  
George Howard ◽  
Rikki M Tanner ◽  
Paul Muntner
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Racial Differences ◽  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Hazard Ratio ◽  
Cvd Risk ◽  
Hazard Ratios ◽  
Stroke Study ◽  
Cvd Mortality

Introduction: Black Americans have higher rates of cardiovascular disease (CVD) mortality compared with whites. Differences in sociodemographic, psychosocial, CVD, and other risk factors may explain increased mortality risk. Methods: We analyzed data from 29,015 REasons for Geographic and Racial Differences in Stroke study participants to determine factors that may explain the higher hazard ratio for CVD and non-CVD mortality in blacks compared with whites. Cause of death was adjudicated by trained investigators. Within age-sex sub-groups, we used Cox proportional hazards regression with progressive adjustment to estimate black:white hazard ratios. Results: Overall, 41.0% of participants were black, and 54.9% were women. Over a mean follow-up of 7.1 years (maximum 12.3 years), 5,299 participants died (1,797 CVD and 3,502 non-CVD deaths). Among participants < 65 years of age, the age and region adjusted black:white hazard ratio for CVD mortality was 2.28 (95% CI: 1.68-3.10) and 2.32 (95% CI: 1.80-3.00) for women and men, respectively, and for participants ≥ 65 was 1.54 (95% CI: 1.30-1.82) and 1.35 (95% CI: 1.16-1.57) for women and men, respectively ( Table ). The higher black:white hazard ratios for CVD mortality were no longer statistically significant after multivariable adjustment, with the largest attenuation occurring with sociodemographic and CVD risk factor adjustment. Among participants < 65 years of age, the age and region adjusted black:white hazard ratios for non-CVD mortality were 1.51 (95% CI: 1.24-1.85) and 1.76 (95% CI: 1.46-2.13) for women and men, respectively, and for participants ≥ 65 was 1.12 (95% CI: 1.00-1.26) and 1.34 (95% CI: 1.20-1.49) for women and men, respectively. The higher black:white hazard ratios for non-CVD mortality were attenuated after adjustment for sociodemographics. Conclusions: Black:white differences are larger for CVD than non-CVD causes of death. The increased CVD mortality for blacks compared with whites is primarily explained by sociodemographic and CVD risk factors.

scholarly journals Differences in Cardiovascular Mortality Risk among African Americans in the Minnesota Heart Survey: 1985-2015 vs The Atherosclerosis Risk in Communities Study Cohort: 1987-2015

2019 ◽  
Vol 29 (1) ◽  
pp. 47-52 ◽  
Author(s):  
Kristen M. George ◽  
Aaron R. Folsom ◽  
Lyn M. Steffen ◽  
Lynne E. Wagenknecht ◽  
Thomas H. Mosley
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
African Americans ◽  
Population Based ◽  
Study Cohort ◽  
Cvd Risk ◽  
Atherosclerosis Risk In Communities ◽  
Hazard Ratios ◽  
Atherosclerosis Risk ◽  
Cvd Mortality

Geographic differences in cardiovascular disease (CVD) mortality among African Americans (AAs) are well-established, but not well-characterized. Using the Minnesota Heart Survey (MHS) and Atherosclerosis Risk in Communities (ARIC) Study, we aimed to assess whether CVD risk factors drive geographic disparities in CVD mortal­ity among AAs.ARIC risk factors were measured be­tween1987-1989 from a population-based sample of AAs, aged 45 to 64 years, living in Jackson, MS and Forsyth County, NC. Simi­lar measures were made at MHS baseline, 1985, in AAs from Minneapolis-St. Paul, MN. CVD mortality was identified using ICD codes for underlying cause of death. We compared MHS and ARIC on CVD death rates using Poisson regression, risk factor prevalences, and hazard ratios using Cox regression.After CVD risk factor adjustment, AA men in MHS had 3.4 (95% CI: 2.1, 4.7) CVD deaths per 1000 person-years vs 9.9 (95% CI: 8.7, 11.1) in ARIC. AA women in MHS had 2.7 (95% CI: 1.8, 3.6) CVD deaths per 1000 person-years vs 6.7 (95% CI: 6.0, 7.4) in ARIC. A 2-fold higher CVD mortality rate remained in ARIC vs MHS after additional adjustment for education and income. ARIC had higher total cholesterol, hypertension, diabetes, and BMI, as well as less education and income than MHS. Risk factor hazard ratios of CVD death did not differ.The CVD death rate was lower in AAs in Minnesota (MHS) than AAs in the South­east (ARIC). While our findings support maintaining low risk for CVD preven­tion, differences in CVD mortality reflect unidentified geographic variation.Ethn Dis. 2019;29(1):47-52; doi:10.18865/ ed.29.1.47

scholarly journals Birthweight in offspring and cardiovascular mortality in their parents, aunts and uncles: a family-based cohort study of 1.35 million births

2019 ◽  
Vol 49 (1) ◽  
pp. 205-215
Author(s):  
Fareeha Shaikh ◽  
Marte Karoline Kjølllesdal ◽  
David Carslake ◽  
Camilla Stoltenberg ◽  
George Davey Smith ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cvd Risk Factors ◽  
Cvd Risk ◽  
Birth Registry ◽  
Nuclear Families ◽  
Hazard Ratios ◽  
Increased Risk ◽  
Paternal Aunt ◽  
Family Based ◽  
Cvd Mortality

Abstract Background A link between suboptimal fetal growth and higher risk of cardiovascular disease (CVD) is well documented. It has been difficult to assess the contribution of environmental versus genetic factors to the association, as these factors are closely connected in nuclear families. We investigated the association between offspring birthweight and CVD mortality in parents, aunts and uncles, and examined whether these associations are explained by CVD risk factors. Methods We linked Norwegian data from the Medical Birth Registry, the Cause of Death Registry and cardiovascular surveys. A total of 1 353 956 births (1967–2012) were linked to parents and one maternal and one paternal aunt/uncle. Offspring birthweight and CVD mortality association among all relationships was assessed by hazard ratios (HR) from Cox regressions. The influence of CVD risk factors on the associations was examined in a subgroup. Results Offspring birthweight was inversely associated with CVD mortality among parents and aunts/uncles. HR of CVD mortality for one standard deviation (SD) increase in offspring birthweight was 0.72 (0.69–0.75) in mothers and 0.89 (0.86–0.92) in fathers. In aunts/uncles, the HRs were between 0.90 (0.86–0.95) and 0.93 (0.91–0.95). Adjustment for CVD risk factors in a subgroup attenuated all the associations. Conclusions Birthweight was associated with increased risk of CVD in parents and in aunts/uncles. These associations were largely explained by CVD risk factors. Our findings suggest that associations between offspring birthweight and CVD in adult relatives involve both behavioural variables (especially smoking) and shared genetics relating to established CVD risk factors.

scholarly journals Black–White Differences in Cardiovascular Disease Mortality: A Prospective US Study, 2003–2017

2020 ◽  
Vol 110 (5) ◽  
pp. 696-703
Author(s):  
Gabriel S. Tajeu ◽  
Monika M. Safford ◽  
George Howard ◽  
Virginia J. Howard ◽  
Ligong Chen ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Socioeconomic Status ◽  
Racial Differences ◽  
Mortality Risk ◽  
Risk Difference ◽  
Cvd Risk Factors ◽  
Cvd Risk ◽  
Mortality Difference ◽  
Cvd Mortality

Objectives. To determine factors that explain the higher Black:White cardiovascular disease (CVD) mortality rates among US adults. Methods. We analyzed data from the Reasons for Geographic and Racial Differences in Stroke study from 2003 to 2017 to estimate Black:White hazard ratios (HRs) for CVD mortality within subgroups younger than 65 years and aged 65 years or older. Results. Among 29 054 participants, 41.0% who were Black and 54.9% who were women, 1549 CVD deaths occurred. Among participants younger than 65 years, the demographic-adjusted Black:White CVD mortality HR was 2.23 (95% confidence interval [CI] = 1.87, 2.65) and 1.21 (95% CI = 1.00, 1.47) after full adjustment. Among participants aged 65 years or older, the demographic-adjusted Black:White CVD mortality HR was 1.58 (95% CI = 1.39, 1.79) and 1.12 (95% CI = 0.97, 1.29) after full adjustment. When we used mediation analysis, socioeconomic status explained 21.2% (95% CI = 13.6%, 31.4%) and 38.0% (95% CI = 20.9%, 61.7%) of the Black:White CVD mortality risk difference among participants younger than 65 years and aged 65 years or older, respectively. CVD risk factors explained 56.6% (95% CI = 42.0%, 77.2%) and 41.3% (95% CI = 22.9%, 65.3%) of the Black:White CVD mortality difference for participants younger than 65 years and aged 65 years or older, respectively. Conclusions. The higher Black:White CVD mortality risk is primarily explained by racial differences in socioeconomic status and CVD risk factors.

Percentage of Age-Predicted Cardiorespiratory Fitness Is Inversely Associated with Cardiovascular Disease Mortality: A Prospective Cohort Study

Cardiology ◽  
2021 ◽  
pp. 1-8
Author(s):  
Jari A. Laukkanen ◽  
Sudhir Kurl ◽  
Hassan Khan ◽  
Francesco Zaccardi ◽  
Setor K. Kunutsor
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Cardiorespiratory Fitness ◽  
Cardiopulmonary Exercise Testing ◽  
Peak Oxygen Uptake ◽  
Standard Deviation Increase ◽  
Hazard Ratios ◽  
Disease Mortality ◽  
Cvd Mortality

<b><i>Introduction:</i></b> Percentage of age-predicted cardiorespiratory fitness (% age-predicted CRF) is a potentially useful cardiopulmonary exercise testing (CPX) parameter, but there are limited data on its prognostic relevance for adverse cardiovascular disease (CVD) outcomes. We aimed to assess the association of % age-predicted CRF with CVD mortality and the extent to which % age-predicted CRF measurements could improve the prediction of CVD mortality. <b><i>Methods:</i></b> Peak oxygen uptake, used as the measure of CRF, was directly assessed in 2,276 men who underwent CPX. The age-predicted CRF estimated from a regression equation for age was transformed to % age-predicted CRF with the following formula: (achieved CRF/age-predicted CRF) × 100. Hazard ratios (HRs) (95% confidence intervals [CIs]) and measures of risk discrimination for CVD mortality were calculated. <b><i>Results:</i></b> During a median follow-up of 28.5 years, 643 fatal CVDs were recorded. The relationship between % age-predicted CRF and CVD mortality was dose response in nature. In analysis adjusted for conventional risk factors, one standard deviation increase in % age-predicted CRF was associated with a reduced risk of CVD mortality (HR 0.61; 95% CI: 0.56–0.67), which was minimally attenuated on further adjustment for several other confounders (HR 0.71; 95% CI: 0.64–0.78). Addition of % age-predicted CRF to a CVD mortality risk prediction model containing established risk factors significantly improved risk discrimination and reclassification. <b><i>Conclusion:</i></b> Percentage of age-predicted CRF is inversely and independently associated with CVD mortality in a graded fashion and significantly improves the prediction and classification of the long-term risk for CVD mortality beyond established risk factors.

Risk prediction of incident coronary heart disease in the Netherlands: re-estimation and improvement of the SCORE risk function

2011 ◽  
Vol 19 (4) ◽  
pp. 840-848 ◽  
Author(s):  
Audrey HH Merry ◽  
Jolanda MA Boer ◽  
Leo J Schouten ◽  
Ton Ambergen ◽  
Ewout W Steyerberg ◽  
...  
Keyword(s):  
Risk Factors ◽  
Coronary Heart Disease ◽  
Risk Prediction ◽  
Risk Function ◽  
Hdl Cholesterol ◽  
Risk Category ◽  
Cholesterol Ratio ◽  
Cholesterol Levels ◽  
C Statistic ◽  
Score Risk

Aims: To re-estimate the SCORE risk function using individual data on risk factors and coronary heart disease (CHD) incidence from the Dutch Cardiovascular Registry Maastricht (CAREMA) population-based cohort study; to evaluate changes that may improve risk prediction after re-estimation; and to compare the performance of the resulting CAREMA risk function with that of existing risk scores. Methods and results: The cohort consisted of 21,148 participants, born in 1927–1977 and randomly sampled from the Maastricht region in 1987–1997. After follow-up (median 10.9 years), 783 incident CHD cases occurred. Model performance was assessed by discrimination and calibration. The additional value of including other risk factors or current risk factors in a different manner was evaluated using the net reclassification index (NRI). The c statistic of the re-estimated SCORE model was 0.799 (95% CI 0.782–0.816). Separating the total/high-density lipoprotein (HDL) cholesterol ratio into total and HDL cholesterol levels did not improve the c statistic ( p = 0.22), but reclassified 6.0% of the participants into a more appropriate risk category ( p < 0.001) compared with the re-estimated model. The resulting CAREMA function reclassified 28% of the participants into a more appropriate risk category than the Framingham score. Compared with the SCORE functions for high- and low-risk regions, the NRIs were 28% and 35%, respectively, which can largely be explained by the difference in outcome definition (CHD incidence vs. CHD mortality). Conclusion: In this Dutch population, a re-estimated SCORE function with total and HDL cholesterol levels instead of the cholesterol ratio can be used for the risk prediction of CHD incidence.

Abstract P107: Differences in Cardiovascular Mortality Risk Among African Americans in the Minnesota Heart Survey, 1985-2015, versus African Americans in the Atherosclerosis Risk in Communities Study (ARIC) Cohort: 1987-2015

Circulation ◽  
2018 ◽  
Vol 137 (suppl_1) ◽  
Author(s):  
Kristen M George ◽  
Aaron R Folsom ◽  
Lyn M Steffen ◽  
Lynne E Wagenknecht ◽  
Thomas H Mosley
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
African Americans ◽  
Mortality Risk ◽  
Total Mortality ◽  
Mortality Rates ◽  
Death Rates ◽  
Hazard Ratios ◽  
Forsyth County ◽  
Cvd Mortality

Geographic differences in CVD mortality across the U.S. are well-established, but frequently overlooked. ARIC enrolled African Americans (AA) from Jackson, MS and Forsyth County, NC, areas of the Southeast with some of the highest CVD mortality rates, especially among AAs. The Minnesota Heart Survey enrolled AAs from Minnesota where CVD rates are among the lowest. However, it is not known whether AAs in Minnesota also have low rates. Using these two cohorts, we assessed whether CVD-related mortality risk among AAs differs by region. Baseline measures of CVD risk factors for MHS were taken in 1985 from a population based sample of AAs, ages 45 to 65, living in the Minneapolis-St. Paul metropolitan area. These same measures were made at ARIC visit 1 (1987-89) in AA participants of the same age residing in Jackson, MS and Forsyth County, NC. CVD and total mortality were identified using ICD codes for underlying cause of death from State and National Death Index records in both cohorts. We compared MHS and ARIC on CVD death rates using Poisson regression, prevalence of risk factors, and risk factor hazard ratios using Cox regression. After risk factor adjustment, AA men in MHS had a rate of 5.2 (95% CI: 3.2, 7.2) CVD deaths per 1000 person-years compared to 15.1 (95% CI: 13.1, 17.1) for AA men in ARIC. For AA women, MHS had 4.1 (95% CI: 2.7, 5.5) CVD deaths per 1000 person-years versus 10.2 (95% CI: 9.0, 11.4) in ARIC. CVD mortality rates were higher in Jackson than Forsyth County within ARIC. CVD death rates paralleled risk factor prevalence at baseline. Compared to MHS, ARIC had significantly higher total cholesterol (215 vs. 202 mg/dL), albeit higher HDL cholesterol (55 vs. 53 mg/dL), as well as higher anti-hypertensive medication use (41 vs. 30%), diabetes (13 vs. 11%) and BMI (30 vs. 29 kg/m 2 ), while smoking did not differ. Despite risk factor differences, hazard ratios of CVD death associated with each risk factor did not differ between studies even after inclusion of a competing risk of non-CVD death. In conclusion, the CVD death rate was lower in AAs in MHS than in AAs residing in the Southeast in ARIC largely due to lower risk factor levels, since the hazard of CVD death for each risk factor did not differ. Study differences reflect incompletely identified geographic variation that need further exploration, especially in the context of health disparities, but support maintaining low risk as a key to CVD prevention.

scholarly journals Province-specific recalibration of CVD risk models using population-specific routine data for Chinese people is important

2021 ◽  
Vol 28 (Supplement_1) ◽  
Author(s):  
D Zhang ◽  
L Pennells ◽  
X Liu ◽  
S Kaptoge ◽  
L Wang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Risk Prediction ◽  
Mortality Risk ◽  
Risk Estimation ◽  
Aggregate Level ◽  
Cvd Risk ◽  
The Future ◽  
Estimation System ◽  
Cvd Mortality

Abstract Funding Acknowledgements Type of funding sources: None. Background Cardiovascular diseases (CVD) are the leading causes of death in China. Since population CVD incidence and risk factor levels vary considerably across regions in China, geo-specific investment in the prevention of CVD could be advantageous. Risk prediction models are an integral part of CVD prevention guidelines and can be used to help guide intervention. However, there is no CVD model generalizable to the various incidence rates, risk-factor levels and composition of CVD in different regions of China. Purpose To construct a CVD risk estimation system, which is calibrated to CVD risk in different regions in China, and can be regularly updated in the future using routinely available aggregate level CVD incidence and risk factor data, in response to changing trends with time and divergent CVD rates. Methods The risk prediction model used was the WHO CVD score, initially calibrated to predict CVD mortality in the whole of mainland China. Further province-specific recalibration was then completed to give models tailored to the 31 provinces. The recalibration approach used aggregate level province, sex- and age group-specific levels of risk factors and CVD mortality. Risk factor values were estimated using 145 268 participants aged 40-80 years old from the China Chronic Disease and Risk Factors Surveillance, a nationally and provincially representative cross-sectional survey in 2015. Province-specific CVD mortality rates in 2017 were estimated based on published scientific reports, unpublished registry data, and health system administrative data. Results Compared with the province-specific models, the China-specific WHO score overestimated mortality risk in some provinces while underestimating risk in others. For example, while the predicted population risk of 10-year CVD mortality was 3.5% in male in both Shanghai and Hebei using the China-specific score (with province-specific observed risk factor values), the province-specific scores gave predicted population risks of 1.1% for Shanghai and 5.5% for Hebei. Accordingly, using the province-specific scores for an individual with the same combination of risk factors, the 10-year risk of CVD mortality differed substantially across provinces. For example, the estimated 10-year risk for a 60 year old, male smoker without diabetes and systolic blood pressure of 140 mmHg and total cholesterol 5 mmol/L ranged from 2.4% in Shanghai to 13.2% in Tibet. Similarly, the estimated 10-year risk for a female with the same risk factor profile ranged from 1.5% in Shanghai to 11.5% in Tibet. Conclusion We have developed a CVD risk estimation system, which is calibrated to CVD risk in different provinces of China, and can be regularly recalibrated in the future using routinely available information. Application of this approach should help accurately estimate CVD risk in individuals from China, and assist policy makers in making more appropriate decisions about allocation of preventative resources. Abstract Figure. Predicted 10 year CVD mortality risk

scholarly journals High risk groups for severe COVID-19 in a whole of population cohort in Australia

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Bette Liu ◽  
Paula Spokes ◽  
Wenqiang He ◽  
John Kaldor
Keyword(s):  
Socioeconomic Status ◽  
New South ◽  
Severe Disease ◽  
Risk Groups ◽  
Prevention Strategies ◽  
Complete Case ◽  
Relative Risks ◽  
South Wales ◽  
Hazard Ratios

Abstract Background Increasing age is the strongest known risk factor for severe COVID-19 disease but information on other factors is more limited. Methods All cases of COVID-19 diagnosed from January–October 2020 in New South Wales Australia were followed for COVID-19-related hospitalisations, intensive care unit (ICU) admissions and deaths through record linkage. Adjusted hazard ratios (aHR) for severe COVID-19 disease, measured by hospitalisation or death, or very severe COVID-19, measured by ICU admission or death according to age, sex, socioeconomic status and co-morbidities were estimated. Results Of 4054 confirmed cases, 468 (11.5%) were classified as having severe COVID-19 and 190 (4.7%) as having very severe disease. After adjusting for sex, socioeconomic status and comorbidities, increasing age led to the greatest risk of very severe disease. Compared to those 30–39 years, the aHR for ICU or death from COVID-19 was 4.45 in those 70–79 years; 8.43 in those 80–89 years; 16.19 in those 90+ years. After age, relative risks for very severe disease associated with other factors were more moderate: males vs females aHR 1.40 (95%CI 1.04–1.88); immunosuppressive conditions vs none aHR 2.20 (1.35–3.57); diabetes vs none aHR 1.88 (1.33–2.67); chronic lung disease vs none aHR 1.68 (1.18–2.38); obesity vs not obese aHR 1.52 (1.05–2.21). More comorbidities was associated with significantly greater risk; comparing those with 3+ comorbidities to those with none, aHR 5.34 (3.15–9.04). Conclusions In a setting with high COVID-19 case ascertainment and almost complete case follow-up, we found the risk of very severe disease varies by age, sex and presence of comorbidities. This variation should be considered in targeting prevention strategies.

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