During the Coronavirus Disease 2019 (COVID-19) pandemic, the number of consultations and diagnoses in primary care and referrals to specialist care declined substantially compared to prepandemic ...levels. Beyond deferral of elective non-COVID-19 care by healthcare providers, it is unclear to what extent healthcare avoidance by community-dwelling individuals contributed to this decline in routine healthcare utilisation. Moreover, it is uncertain which specific symptoms were left unheeded by patients and which determinants predispose to healthcare avoidance in the general population. In this cross-sectional study, we assessed prevalence of healthcare avoidance during the pandemic from a patient perspective, including symptoms that were left unheeded, as well as determinants of healthcare avoidance.
On April 20, 2020, a paper COVID-19 survey addressing healthcare utilisation, socioeconomic factors, mental and physical health, medication use, and COVID-19-specific symptoms was sent out to 8,732 participants from the population-based Rotterdam Study (response rate 73%). All questionnaires were returned before July 10, 2020. By hand, prevalence of healthcare avoidance was subsequently verified through free text analysis of medical records of general practitioners. Odds ratios (ORs) for avoidance were determined using logistic regression models, adjusted for age, sex, and history of chronic diseases. We found that 1,142 of 5,656 included participants (20.2%) reported having avoided healthcare. Of those, 414 participants (36.3%) reported symptoms that potentially warranted urgent evaluation, including limb weakness (13.6%), palpitations (10.8%), and chest pain (10.2%). Determinants related to avoidance were older age (adjusted OR 1.14 95% confidence interval (CI) 1.08 to 1.21), female sex (1.58 1.38 to 1.82), low educational level (primary education versus higher vocational/university 1.21 1.01 to 1.46), poor self-appreciated health (per level decrease 2.00 1.80 to 2.22), unemployment (versus employed 2.29 1.54 to 3.39), smoking (1.34 1.08 to 1.65), concern about contracting COVID-19 (per level increase 1.28 1.19 to 1.38) and symptoms of depression (per point increase 1.13 1.11 to 1.14) and anxiety (per point increase 1.16 1.14 to 1.18). Study limitations included uncertainty about (perceived) severity of the reported symptoms and potentially limited generalisability given the ethnically homogeneous study population.
In this population-based cross-sectional study, 1 in 5 individuals avoided healthcare during lockdown in the COVID-19 pandemic, often for potentially urgent symptoms. Healthcare avoidance was strongly associated with female sex, fragile self-appreciated health, and high levels of depression and anxiety. These results emphasise the need for targeted public education urging these vulnerable patients to timely seek medical care for their symptoms to mitigate major health consequences.
Non-communicable diseases (NCDs) are leading causes of premature disability and death worldwide. However, the lifetime risk of developing any NCD is unknown, as are the effects of shared common risk ...factors on this risk.
Between July 6, 1989, and January 1, 2012, we followed participants from the prospective Rotterdam Study aged 45 years and older who were free from NCDs at baseline for incident stroke, heart disease, diabetes, chronic respiratory disease, cancer, and neurodegenerative disease. We quantified occurrence/co-occurrence and remaining lifetime risk of any NCD in a competing risk framework. We additionally studied the lifetime risk of any NCD, age at onset, and overall life expectancy for strata of 3 shared risk factors at baseline: smoking, hypertension, and overweight. During 75,354 person-years of follow-up from a total of 9,061 participants (mean age 63.9 years, 60.1% women), 814 participants were diagnosed with stroke, 1,571 with heart disease, 625 with diabetes, 1,004 with chronic respiratory disease, 1,538 with cancer, and 1,065 with neurodegenerative disease. NCDs tended to co-occur substantially, with 1,563 participants (33.7% of those who developed any NCD) diagnosed with multiple diseases during follow-up. The lifetime risk of any NCD from the age of 45 years onwards was 94.0% (95% CI 92.9%-95.1%) for men and 92.8% (95% CI 91.8%-93.8%) for women. These risks remained high (>90.0%) even for those without the 3 risk factors of smoking, hypertension, and overweight. Absence of smoking, hypertension, and overweight was associated with a 9.0-year delay (95% CI 6.3-11.6) in the age at onset of any NCD. Furthermore, the overall life expectancy for participants without these risk factors was 6.0 years (95% CI 5.2-6.8) longer than for those with all 3 risk factors. Participants aged 45 years and older without the 3 risk factors of smoking, hypertension, and overweight at baseline spent 21.6% of their remaining lifetime with 1 or more NCDs, compared to 31.8% of their remaining life for participants with all of these risk factors at baseline. This difference corresponds to a 2-year compression of morbidity of NCDs. Limitations of this study include potential residual confounding, unmeasured changes in risk factor profiles during follow-up, and potentially limited generalisability to different healthcare settings and populations not of European descent.
Our study suggests that in this western European community, 9 out of 10 individuals aged 45 years and older develop an NCD during their remaining lifetime. Among those individuals who develop an NCD, at least a third are subsequently diagnosed with multiple NCDs. Absence of 3 common shared risk factors is associated with compression of morbidity of NCDs. These findings underscore the importance of avoidance of these common shared risk factors to reduce the premature morbidity and mortality attributable to NCDs.
The 2013 American College of Cardiology/American Heart Association (ACC/AHA) guidelines introduced a prediction model and lowered the threshold for treatment with statins to a 7.5% 10-year hard ...atherosclerotic cardiovascular disease (ASCVD) risk. Implications of the new guideline's threshold and model have not been addressed in non-US populations or compared with previous guidelines.
To determine population-wide implications of the ACC/AHA, the Adult Treatment Panel III (ATP-III), and the European Society of Cardiology (ESC) guidelines using a cohort of Dutch individuals aged 55 years or older.
We included 4854 Rotterdam Study participants recruited in 1997-2001. We calculated 10-year risks for "hard" ASCVD events (including fatal and nonfatal coronary heart disease CHD and stroke) (ACC/AHA), hard CHD events (fatal and nonfatal myocardial infarction, CHD mortality) (ATP-III), and atherosclerotic CVD mortality (ESC).
Events were assessed until January 1, 2012. Per guideline, we calculated proportions of individuals for whom statins would be recommended and determined calibration and discrimination of risk models.
The mean age was 65.5 (SD, 5.2) years. Statins would be recommended for 96.4% (95% CI, 95.4%-97.1%; n = 1825) of men and 65.8% (95% CI, 63.8%-67.7%; n = 1523) of women by the ACC/AHA, 52.0% (95% CI, 49.8%-54.3%; n = 985) of men and 35.5% (95% CI, 33.5%-37.5%; n = 821) of women by the ATP-III, and 66.1% (95% CI, 64.0%-68.3%; n = 1253) of men and 39.1% (95% CI, 37.1%-41.2%; n = 906) of women by ESC guidelines. With the ACC/AHA model, average predicted risk vs observed cumulative incidence of hard ASCVD events was 21.5% (95% CI, 20.9%-22.1%) vs 12.7% (95% CI, 11.1%-14.5%) for men (192 events) and 11.6% (95% CI, 11.2%-12.0%) vs 7.9% (95% CI, 6.7%-9.2%) for women (151 events). Similar overestimation occurred with the ATP-III model (98 events in men and 62 events in women) and ESC model (50 events in men and 37 events in women). The C statistic was 0.67 (95% CI, 0.63-0.71) in men and 0.68 (95% CI, 0.64-0.73) in women for hard ASCVD (ACC/AHA), 0.67 (95% CI, 0.62-0.72) in men and 0.69 (95% CI, 0.63-0.75) in women for hard CHD (ATP-III), and 0.76 (95% CI, 0.70-0.82) in men and 0.77 (95% CI, 0.71-0.83) in women for CVD mortality (ESC).
In this European population aged 55 years or older, proportions of individuals eligible for statins differed substantially among the guidelines. The ACC/AHA guideline would recommend statins for nearly all men and two-thirds of women, proportions exceeding those with the ATP-III or ESC guidelines. All 3 risk models provided poor calibration and moderate to good discrimination. Improving risk predictions and setting appropriate population-wide thresholds are necessary to facilitate better clinical decision making.
Atherosclerotic cardiovascular disease (ASCVD) is driven by multifaceted contributions of the immune system. However, the dysregulation of immune cells that leads to ASCVD is poorly understood. We ...determined the association of components of innate and adaptive immunity longitudinally with ASCVD, and assessed whether arterial calcifications play a role in this association.
Granulocyte (innate immunity) and lymphocyte (adaptive immunity) counts were determined 3 times (2002-2008, mean age 65.2 years; 2009-2013, mean age 69.0 years; and 2014-2015, mean age 78.5 years) in participants of the population-based Rotterdam Study without ASCVD at baseline. Participants were followed-up for ASCVD or death until 1 January 2015. A random sample of 2,366 underwent computed tomography at baseline to quantify arterial calcification volume in 4 vessel beds. We studied the association between immunity components with risk of ASCVD and assessed whether immunity components were related to arterial calcifications at baseline. Of 7,730 participants (59.4% women), 801 developed ASCVD during a median follow-up of 8.1 years. Having an increased granulocyte count increased ASCVD risk (adjusted hazard ratio for doubled granulocyte count 95% CI = 1.78 1.34-2.37, P < 0.001). Higher granulocyte counts were related to larger calcification volumes in all vessels, most prominently in the coronary arteries (mean difference in calcium volume mm3 per SD increase in granulocyte count 95% CI = 32.3 9.9-54.7, P < 0.001). Respectively, the association between granulocyte count and incident coronary heart disease and stroke was partly mediated by coronary artery calcification (overall proportion mediated 95% CI = 19.0% -10% to 32.3%, P = 0.08) and intracranial artery calcification (14.9% -10.9% to 19.1%, P = 0.05). A limitation of our study is that studying the etiology of ASCVD remains difficult within an epidemiological setting due to the limited availability of surrogates for innate and especially adaptive immunity.
In this study, we found that an increased granulocyte count was associated with a higher risk of ASCVD in the general population. Moreover, higher levels of granulocytes were associated with larger volumes of arterial calcification. Arterial calcifications may explain a proportion of the link between granulocytes and ASCVD.
Identification of individuals at high risk of dementia is essential for development of prevention strategies, but reliable tools are lacking for risk stratification in the population. The authors ...developed and validated a prediction model to calculate the 10-year absolute risk of developing dementia in an aging population.
In a large, prospective population-based cohort, data were collected on demographic, clinical, neuropsychological, genetic, and neuroimaging parameters from 2,710 nondemented individuals age 60 or older, examined between 1995 and 2011. A basic and an extended model were derived to predict 10-year risk of dementia while taking into account competing risks from death due to other causes. Model performance was assessed using optimism-corrected C-statistics and calibration plots, and the models were externally validated in the Dutch population-based Epidemiological Prevention Study of Zoetermeer and in the Alzheimer's Disease Neuroimaging Initiative cohort 1 (ADNI-1).
During a follow-up of 20,324 person-years, 181 participants developed dementia. A basic dementia risk model using age, history of stroke, subjective memory decline, and need for assistance with finances or medication yielded a C-statistic of 0.78 (95% CI=0.75, 0.81). Subsequently, an extended model incorporating the basic model and additional cognitive, genetic, and imaging predictors yielded a C-statistic of 0.86 (95% CI=0.83, 0.88). The models performed well in external validation cohorts from Europe and the United States.
In community-dwelling individuals, 10-year dementia risk can be accurately predicted by combining information on readily available predictors in the primary care setting. Dementia prediction can be further improved by using data on cognitive performance, genotyping, and brain imaging. These models can be used to identify individuals at high risk of dementia in the population and are able to inform trial design.
The exact etiology of dementia is still unclear, but both genetic and lifestyle factors are thought to be key drivers of this complex disease. The recognition of familial patterns of dementia has led ...to the discovery of genetic factors that have a role in the pathogenesis of dementia, including the apolipoprotein E (APOE) genotype and a large and still-growing number of genetic variants
. Beyond genetic architecture, several modifiable risk factors have been implicated in the development of dementia
. Prevention trials of measures to halt or delay cognitive decline are increasingly recruiting older individuals who are genetically predisposed to dementia. However, it remains unclear whether targeted health and lifestyle interventions can attenuate or even offset increased genetic risk. Here, we leverage long-term data on both genetic and modifiable risk factors from 6,352 individuals aged 55 years and older in the population-based Rotterdam Study. In this study, we demonstrate that, in individuals at low and intermediate genetic risk, favorable modifiable-risk profiles are related to a lower risk of dementia compared to unfavorable profiles. In contrast, these protective associations were not found in those at high genetic risk.
The net reclassification improvement (NRI) is an increasingly popular measure for evaluating improvements in risk predictions. This article details a review of 67 publications in high-impact general ...clinical journals that considered the NRI. Incomplete reporting of NRI methods, incorrect calculation, and common misinterpretations were found. To aid improved applications of the NRI, the article elaborates on several aspects of the computation and interpretation in various settings. Limitations and controversies are discussed, including the effect of miscalibration of prediction models, the use of the continuous NRI and “clinical NRI,” and the relation with decision analytic measures. A systematic approach toward presenting NRI analysis is proposed: Detail and motivate the methods used for computation of the NRI, use clinically meaningful risk cutoffs for the category-based NRI, report both NRI components, address issues of calibration, and do not interpret the overall NRI as a percentage of the study population reclassified. Promising NRI findings need to be followed with decision analytic or formal cost-effectiveness evaluations.
Trial emulations in observational data analyses can complement findings from randomized clinical trials, inform future trial designs, or generate evidence when randomized studies are not feasible due ...to resource constraints and ethical or practical limitations. Importantly, trial emulation designs facilitate causal inference in observational data analyses by enhancing counterfactual thinking and comparisons of real-world observations (e.g. Mendelian Randomization) to hypothetical interventions. In order to enhance credibility, trial emulations would benefit from prospective registration, publication of statistical analysis plans, and subsequent prospective benchmarking to randomized clinical trials prior to their publication. Confounding by indication, however, is the key challenge to interpreting observed intended effects of an intervention as causal in observational data analyses. We discuss the target trial emulation of the REDUCE-AMI randomized clinical trial (ClinicalTrials.gov ID NCT03278509; beta-blocker use in patients with preserved left ventricular ejection fraction after myocardial infarction) to illustrate the challenges and uncertainties of studying intended effects of interventions without randomization to account for confounding. We furthermore directly compare the findings, statistical power, and clinical interpretation of the results of the REDUCE-AMI target trial emulation to those from the simultaneously published randomized clinical trial. The complexity and subtlety of confounding by indication when studying intended effects of interventions can generally only be addressed by randomization.
Data are scarce for the lifetime risk of developing impaired glucose metabolism, including prediabetes, as are data for the risk of eventual progression from prediabetes to diabetes and for ...initiation of insulin treatment in previously untreated patients with diabetes. We aimed to calculate the lifetime risk of the full range of glucose impairments, from normoglycaemia to prediabetes, type 2 diabetes, and eventual insulin use.
In this prospective population-based cohort analysis, we used data from the population-based Rotterdam Study. We identified diagnostic events by use of general practitioners' records, hospital discharge letters, pharmacy dispensing data, and serum fasting glucose measurements taken at the study centre (Rotterdam, Netherlands) visits. Normoglycaemia, prediabetes, and diabetes were defined on the basis of WHO criteria for fasting glucose (normoglycaemia: ≤6·0 mmol/L; prediabetes: >6·0 mmol/L and <7·0 mmol/L; and diabetes ≥7·0 mmol/L or use of glucose-lowering drug). We calculated lifetime risk using a modified version of survival analysis adjusted for the competing risk of death. We also estimated the lifetime risk of progression from prediabetes to overt diabetes and from diabetes free of insulin treatment to insulin use. Additionally, we calculated years lived with healthy glucose metabolism.
We used data from 10 050 participants from the Rotterdam Study. During a follow-up of up to 14·7 years (between April 1, 1997, and Jan 1, 2012), 1148 participants developed prediabetes, 828 developed diabetes, and 237 started insulin treatment. At age 45 years, the remaining lifetime risk was 48·7% (95% CI 46·2-51·3) for prediabetes, 31·3% (29·3-33·3) for diabetes, and 9·1% (7·8-10·3) for insulin use. In individuals aged 45 years, the lifetime risk to progress from prediabetes to diabetes was 74·0% (95% CI 67·6-80·5), and 49·1% (38·2-60·0) of the individuals with overt diabetes at this age started insulin treatment. The lifetime risks attenuated with advancing age, but increased with increasing BMI and waist circumference. On average, individuals with severe obesity lived 10 fewer years without glucose impairment compared with normal-weight individuals.
Impaired glucose metabolism is a substantial burden on population health, and our findings emphasise the need for more effective prevention strategies, which should be implemented as soon in a person's life as possible. The substantial lifetime risk of prediabetes and diabetes in lean individuals also supports risk factor control in non-obese individuals.
Erasmus MC and Erasmus University Rotterdam; Netherlands Organisation for Scientific Research; Netherlands Organisation for Health Research and Development; Research Institute for Diseases in the Elderly; Netherlands Genomics Initiative; Netherlands Ministry of Education, Culture and Science; Netherlands Ministry of Health, Welfare and Sports; European Commission; and Municipality of Rotterdam.
The prevalence of cardiovascular diseases is rising. Therefore, adequate risk prediction and identification of its determinants is increasingly important. The Rotterdam Study is a prospective ...population-based cohort study ongoing since 1990 in the city of Rotterdam, The Netherlands. One of the main targets of the Rotterdam Study is to identify the determinants and prognosis of cardiovascular diseases. Case finding in epidemiological studies is strongly depending on various sources of followup and clear outcome definitions. The sources used for collection of data in the Rotterdam Study are diverse and the definitions of outcomes in the Rotterdam Study have changed due to the introduction of novel diagnostics and therapeutic interventions. This article gives the methods for data collection and the up-to-date definitions of the cardiac outcomes based on international guidelines, including the recently adopted cardiovascular disease mortality definitions. In all, detailed description of cardiac outcome definitions enhances the possibility to make comparisons with other studies in the field of cardiovascular research and may increase the strength of collaborations.
PDF
