Becoming the Framingham Study 1947-1950

The Cantabria Cohort, a protocol for a population-based cohort in northern Spain

Cantabria Cohort stems from a research and action initiative lead by researchers from Valdecilla Research Institute (IDIVAL), Marqués de Valdecilla University Hospital and University of Cantabria, supported by the regional Goverment. Its aim is to identify and follow up a cohort that would provide information to improve the understanding of the etiology and prognosis of different acute and chronic diseases. The Cantabria Cohort will recruit between 40,000-50,000 residents aged 40-69 years at baseline, representing 10-20% of the target population. Currently, more than 30,000 volunteers have been enrolled. All participants will be invited for a re-assessment every three years, while the overall duration is planned for twenty years. The repeated collection of biomaterials combined with broad information from participant questionnaires, medical examinations, actual health system records and other secondary public data sources is a major strength of its design, which will make it possible to address biological pathways of disease development, identify new factors involved in health and disease, design new strategies for disease prevention, and advance precision medicine. It is conceived to allow access to a large number of researchers worldwide to boost collaboration and medical research.

Health Literacy and Perceived Control: Intermediary Factors in the Relationship Between Race and Cardiovascular Disease Risk in Incarcerated Men in the United States

BACKGROUND

Black race, inadequate health literacy, and poor perceived control are predictors of increased cardiovascular disease (CVD) risk. The purpose of this study was to explore the relationships among race, health literacy, perceived control, and CVD risk while controlling for known risk factors in incarcerated men.

METHODS

We included data from 349 incarcerated men to examine race and CVD risk (Framingham Risk Score) using a serial mediation model with health literacy and perceived control using 95% confidence intervals (CIs) from 5000 bootstrap samples.

RESULTS

Of the participants (age, 36 ± 10; education, 12 ± 2; body mass index, 28.3 ± 5.0), 64.2% were White and 35.8% were Black. Black incarcerated men were younger (P = .047) with lower levels of health literacy (P < .001). All 3 indirect effects of race on CVD were significant, whereas the direct effect of race was not. Black incarcerated men had higher levels of CVD risk through health literacy (a1b1 = 0.3571; 95% CI, 0.0948-0.7162) and lower levels of CVD risk through perceived control (a2b2 = -0.1855; 95% CI, -0.4388 to -0.0077). Black incarcerated men had higher levels of CVD risk through health literacy influenced by perceived control (a1b2d21 = 0.0627; 95% CI, 0.0028-0.1409), indicating that despite the protective effect of higher levels of perceived control in Black incarcerated men, CVD risk remained higher compared with their White counterparts.

CONCLUSION

Future CVD risk reduction interventions in incarcerated men, specifically Black incarcerated men, should include goals of improving health literacy and perceived control as modifiable risk factors.

Francis Carter Wood and the birth of population-based cancer surveillance

The founding of the National Cancer Institute in 1937 was attended by the formation of the National Advisory Council on Cancer. A seminal action by this Council was the funding of the First National Cancer Survey, the first population-based cancer surveillance activity of the federal government. Francis Carter Wood, distinguished cancer researcher and editor of the American Journal of Cancer (predecessor to Cancer Research), was a member of that Council, through which he was a prime mover in the funding of this survey. This action reflected Wood's commitment to population-based cancer surveillance, voiced over more than 2 decades. Such commitment reflected his view that only such data could identify the optimal treatment modality for cancer patients. The implications of this view, with epidemiologic data providing insights on treatment rather than prevention of disease, as the basis for the development of cancer epidemiology are then considered.

Risk Prediction in Patients With Heart Failure With Preserved Ejection Fraction Using Gene Expression Data and Machine Learning

Heart failure with preserved ejection fraction (HFpEF) has become a major health issue because of its high mortality, high heterogeneity, and poor prognosis. Using genomic data to classify patients into different risk groups is a promising method to facilitate the identification of high-risk groups for further precision treatment. Here, we applied six machine learning models, namely kernel partial least squares with the genetic algorithm (GA-KPLS), the least absolute shrinkage and selection operator (LASSO), random forest, ridge regression, support vector machine, and the conventional logistic regression model, to predict HFpEF risk and to identify subgroups at high risk of death based on gene expression data. The model performance was evaluated using various criteria. Our analysis was focused on 149 HFpEF patients from the Framingham Heart Study cohort who were classified into good-outcome and poor-outcome groups based on their 3-year survival outcome. The results showed that the GA-KPLS model exhibited the best performance in predicting patient risk. We further identified 116 differentially expressed genes (DEGs) between the two groups, thus providing novel therapeutic targets for HFpEF. Additionally, the DEGs were enriched in Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways related to HFpEF. The GA-KPLS-based HFpEF model is a powerful method for risk stratification of 3-year mortality in HFpEF patients.

Subtypes identification on heart failure with preserved ejection fraction via network enhancement fusion using multi-omics data

Heart failure with preserved ejection fraction (HFpEF) is associated with multiple etiologic and pathophysiologic factors. HFpEF leads to significant cardiovascular morbidity and mortality. There are various reasons that fail to identify effective therapeutic interventions for HFpEF, primarily due to its clinical heterogeneity causing significant difficulties in determining physiologic and prognostic implications for this syndrome. Thus, identifying clinical subtypes using multi-omics data has great implications for efficient treatment and prognosis of HFpEF patients. Here we proposed to integrate mRNA, DNA methylation and microRNA (miRNA) expression data of HFpEF with a similarity network fusion (SNF) method following a network enhancement (ne-SNF) denoising technique to form a fused network. A spectral clustering method was then used to obtain clusters of patient subtypes. Experiments on HFpEF datasets demonstrated that ne-SNF significantly outperforms single data subtype analysis and other integrated methods. The identified subgroups were shown to have statistically significant differences in survival. Two HFpEF subtypes were defined: a high-risk group (16.8%) and a low-risk group (83.2%). The 5-year mortality rates were 63.3% and 33.0% for the high- and low-risk group, respectively. After adjusting for the effects of clinical covariates, HFpEF patients in the high-risk group were 2.43 times more likely to die than the low-risk group. A total of 157 differentially expressed (DE) mRNAs, 2199 abnormal methylations and 121 DE miRNAs were identified between two subtypes. They were also enriched in many HFpEF-related biological processes or pathways. The ne-SNF method provides a novel pipeline for subtype identification in integrated analysis of multi-omics data.

Disparities in Cardiovascular Research Output and Disease Outcomes among High-, Middle- and Low-Income Countries - An Analysis of Global Cardiovascular Publications over the Last Decade (2008-2017)

Background

Cardiovascular disease (CVD) is the leading cause of death and disability worldwide. Health research is crucial to managing disease burden. Previous work has highlighted marked discrepancies in research output and disease burden between high-income countries (HICs) and low- and lower-middle-income countries (LI-LMICs) and there is little data to understand whether this gap has bridged in recent years. We conducted a global, country level bibliometric analysis of CVD publications with respect to trends in disease burden and county development indicators.

Methods

A search filter with a precision and recall of 0.92 and 0.91 respectively was developed to extract cardiovascular publications from the Web of Science (WOS) for the years 2008-2017. Data for disease burden and country development indicators were extracted from the Global Burden of Disease and the World Bank database respectively.

Results

Our search revealed 847,708 CVD publications for the period 2008-17, with a 43.4% increase over the decade. HICs contributed 81.1% of the global CVD research output and accounted for 8.1% and 8.5% of global CVD DALY losses deaths respectively. LI-LMICs contributed 2.8% of the total output and accounted for 59.5% and 57.1% global CVD DALY losses and death rates.

Conclusions

A glaring disparity in research output and disease burden persists. While LI-LMICs contribute to the majority of DALYs and mortality from CVD globally, their contribution to research output remains the lowest. These data call on national health budgets and international funding support to allocate funds to strengthen research capacity and translational research to impact CVD burden in LI-LMICs.

Obesity, cardiovascular risk and healthcare resource utilization in the UK

Aims

Obesity and cardiovascular diseases (CVDs) often co-occur, likely increasing the intensity of healthcare resource utilization (HCRU). This retrospective, observational database study examined the joint effect of obesity and cardiovascular risk status on HCRU and compared HCRU between body mass index (BMI) categories and CVD-risk categories in the UK.

Methods

Patient demographics and data on CVD and BMI were obtained from the UK Clinical Practice Research Datalink. Cardiovascular risk status, calculated using the Framingham Risk Equation, was used to categorize people into high-risk and low-risk groups, while a CVD diagnosis was used to define the established CVD group. Patients were split into BMI categories using the standard World Health Organization classifications. For each CVD and BMI category, mean number and costs of general practitioner contacts, hospital admissions and prescriptions were estimated.

Results

The final study population included 1,600,709 patients. Data on CVD status were available on just over one-quarter of the sample (28.6%) and BMI data for just less than half (43.2%). The number of general practitioner contacts and prescriptions increased with increasing BMI category for each of the three CVD-risk groups. The group with established CVD had the greatest utilization of all components of healthcare resource, followed by high CVD risk then low CVD-risk groups.

Conclusion

Increasing BMI category and CVD-risk status both affected several HCRU components. These findings highlight the importance of timely obesity management and treatment of CVD-risk factors as a means of preventing increasing HCRU.

Low Carbohydrate and Low-Fat Diets: What We Don't Know and Why we Should Know It

In the 1940s, the diet-heart hypothesis proposed that high dietary saturated fat and cholesterol intake promoted coronary heart disease in "at-risk" individuals. This hypothesis prompted federal recommendations for a low-fat diet for "high risk" patients and as a preventive health measure for everyone except infants. The low carbohydrate diet, first used to treat type 1 diabetes, became a popular obesity therapy with the Atkins diet in the 1970s. Its predicted effectiveness was based largely on the hypothesis that insulin is the causa prima of weight gain and regain via hyperphagia and hypometabolism during and after weight reduction, and therefore reduced carbohydrate intake would promote and sustain weight loss. Based on literature reviews, there are insufficient randomized controlled inpatient studies examining the physiological significance of the mechanisms proposed to support one over the other. Outpatient studies can be confounded by poor diet compliance such that the quality and quantity of the energy intake cannot be ascertained. Many studies also fail to separate macronutrient quantity from quality. Overall, there is no conclusive evidence that the degree of weight loss or the duration of reduced weight maintenance are significantly affected by dietary macronutrient quantity beyond effects attributable to caloric intake. Further work is needed.

Downsizing obesity: On Ancel Keys, the origins of BMI, and the neglect of excess weight as a health hazard in the United States from the 1950s to 1970s

In 1972 Body Mass Index, BMI was put forth by physiologist Ancel Keys in his analysis of Seven Countries Study heart disease epidemiological data as the best available measure of obesity. This work culminated more than 20 years of effort by Keys to discredit the accepted measure of obesity, weight relative to height, along with a major public health campaign in the United States to fight heart disease through weight control. Here, I retrace his campaign to replace weight as a measure of obesity and analyze its methodology and relationship to the broader research field of heart disease epidemiology. I also explore why the epidemiological community accepted BMI despite Keys's failure to demonstrate that either it or adiposity (body fat content), were superior as predictors of heart disease-one of the Seven Countries Study's central aims.

Myocardial infarction and death findings from a 22-year follow-up of a cohort of 980 employed Swedish men

OBJECTIVES

In this article, we present death and myocardial infarction (MI) incidences over 22 years in relation to possible risk factors and their explanatory value.

STUDY DESIGN

In 1993, 980 middle-aged Swedish men in an automotive industry were surveyed at a health checkup as part of the Renault-Volvo Coeur project. The Swedish cohort was revisited in 2015.

METHODS

In 2015, incident MIs were identified using postal questionnaires, hospital records, and the Swedish national MI and death registers. The statistical results were given as odds ratios (ORs) and pseudo-R² (PR²), showing the proportion of variation in risk explained by logistic models.

RESULTS

One hundred and four deaths (4.6 per 1000 person-years) and 89 first MIs (4.2 per 1000 person-years) were identified. The Framingham risk index showed the strongest association with MI (OR = 23; 95% confidence interval [CI] = 5.42, 96.9), comparing the fifth quintile with the first. The all-cause death showed an OR of 3.2 (95% CI = 1.65, 6.08), with a suggested U-shape over quintiles. The percentages of PR² for MI and death were 8.8% and 6.6%, respectively. All risk factors together explained 22% of the variation in risk of MI. Comparing mortality in men living alone with those married yielded an OR of 3.78, which was found to be statistically significant. The corresponding OR for MI was not significant.

CONCLUSIONS

Traditional risk factors were confirmed but explained a modest proportion of the risk variation.

Patients-in-waiting or chronically healthy individuals? People with elevated cholesterol talk about risk

Risk adopts an ambiguous position between health and illness/disease and is culturally salient in various health-related everyday practices. Previous research on risk experience has mostly focused on the illness/disease side of this risk ambiguity. Persons at risk have typically been defined as patients (of some kind) and their condition as a form of proto-illness. To allow for the cultural proliferation of health risk and to account for the health side of risk ambiguity, I chose to focus on elevated cholesterol, a condition both intensely medicalised and connected to the everyday practice of eating, among participants (n = 14) recruited from a consumer panel and approached not as patients, but as individuals concerned about their cholesterol. Utilising the biographical disruption framework developed by Bury, I show how the risk experience of my participants differed from the chronic illness experience. Instead of patients-in-waiting suffering from a proto-illness, they presented themselves as 'chronically healthy individuals' (Varul 2010), actively trying to avoid becoming patients through a responsible regimen of personal health care. The results call for a more nuanced approach to the risk experience, which accounts for both sides of the risk ambiguity.

Systematic Review of Validity Assessments of Framingham Risk Score Results in Health Economic Modelling of Lipid-Modifying Therapies in Europe

BACKGROUND

The Framingham Risk Score is used both in the clinical setting and in health economic analyses to predict the risk for future coronary heart disease events. Based on an American population, the Framingham Risk Score has been criticised for potential overestimation of risk in European populations.

OBJECTIVE

We investigated whether the use of the Framingham Risk Score actually was validated in health economic studies that modelled the effects of lipid-lowering treatment with statins on coronary heart disease events in European populations.

METHODS

In this systematic literature review of all relevant published studies in English (literature searched September 2016 in PubMed, EMBASE and SCOPUS), 99 studies were identified and 22 were screened in full text, 18 of which were included. Key data were extracted and synthesised narratively.

RESULTS

The only type of validation identified was a comparison against coronary heart disease risk data from one primary preventive and one secondary preventive clinical investigation, and from observational population data in one study. Taken together, those three studies reported an overall satisfactory accuracy in the results obtained by Framingham Risk Score predictions, but the Framingham Risk Score tended to underestimate non-fatal myocardial infarctions. In five studies, potential issues in applying the Framingham Risk Score on a European population were not addressed.

CONCLUSION

Further studies are needed to ascertain that the Framingham Risk Score can accurately predict cardiovascular outcome in health economic modelling studies on lipid-lowering therapy in European populations. Future modelling studies using the Framingham Risk Score would benefit from validating the results against other data.

Contesting lifestyle risk and gendering coronary candidacy: lay epidemiology of heart disease in Finland in the 1970s

This study addresses two issues currently under critical discussion in the epidemiology of cardiovascular diseases (CVD), the relative neglect of women and the individualised nature of key risk factors. It focuses on the North Karelia project (NKP), a community programme aimed at coronary heart disease (CHD) prevention in a predominantly rural Finnish region in the early 1970s, that is, during a period when the epidemiological understanding of CVD still was relatively new and actively promoted. Adopting the notions of lay epidemiology and coronary candidacy, culturally mediated explanatory models lay people use to assess who is likely to develop heart disease and why, the study shows that locals targeted by the project critically engaged with both of these bias. Based on the rich materials resulting from project activities the study shows, first, how many locals subsumed the individualised and lifestyle-based approach to CHD prevention promoted by NKP under a more general framework emphasising the health effects of ongoing structural changes in the area, and second, how women constructed themselves as viable coronary candidates. The case supports the position in the current discussions on lay expertise that wants to integrate lay experiences more firmly into epidemiological studies and public health.

Molecular epidemiology of infectious diseases

Molecular epidemiology (ME) is a branch of epidemiology developed by merging molecular biology into epidemiological studies. In this paper, the authors try to discuss the ways that molecular epidemiology studies identify infectious diseases' causation and pathogenesis, and unravel infectious agents' sources, reservoirs, circulation pattern, transmission pattern, transmission probability, and transmission order. They bring real-world examples of research works in each area to make each study design more understandable. They also address some research areas and study design aspects that need further attention in future. They close with some thoughts about future directions in this field and emphasize on the need for training competent molecular epidemiology specialists that are capable of dealing with rapid advances in the field.

Cohort Profile: The Framingham Heart Study (FHS): overview of milestones in cardiovascular epidemiology

The Framingham Heart Study (FHS) has conducted seminal research defining cardiovascular disease (CVD) risk factors and fundamentally shaping public health guidelines for CVD prevention over the past five decades. The success of the Original Cohort, initiated in 1948, paved the way for further epidemiological research in preventive cardiology. Due to the keen observations suggesting the role of shared familial factors in the development of CVD, in 1971 the FHS began enroling the second generation cohort, comprising the children of the Original Cohort and the spouses of the children. In 2002, the third generation cohort, comprising the grandchildren of the Original Cohort, was initiated to additionally explore genetic contributions to CVD in greater depth. Additionally, because of the predominance of White individuals of European descent in the three generations of FHS participants noted above, the Heart Study enrolled the OMNI1 and OMNI2 cohorts in 1994 and 2003, respectively, aimed to reflect the current greater racial and ethnic diversity of the town of Framingham. All FHS cohorts have been examined approximately every 2-4 years since the initiation of the study. At these periodic Heart Study examinations, we obtain a medical history and perform a cardiovascular-focused physical examination, 12-lead electrocardiography, blood and urine samples testing and other cardiovascular imaging studies reflecting subclinical disease burden.The FHS has continually evolved along the cutting edge of cardiovascular science and epidemiological research since its inception. Participant studies now additionally include study of cardiovascular imaging, serum and urine biomarkers, genetics/genomics, proteomics, metabolomics and social networks. Numerous ancillary studies have been established, expanding the phenotypes to encompass multiple organ systems including the lungs, brain, bone and fat depots, among others. Whereas the FHS was originally conceived and designed to study the epidemiology of cardiovascular disease, it has evolved over the years with staggering expanded breadth and depth that have far greater implications in the study of the epidemiology of a wide spectrum of human diseases. The FHS welcomes research collaborations using existing or new collection of data. Detailed information regarding the procedures for research application submission and review are available at [http://www.framinghamheartstudy.org/researchers/index.php].

National Surveys of Population Health: Big Data Analytics for Mobile Health Monitors

At the core of the healthcare crisis is fundamental lack of actionable data. Such data could stratify individuals within populations to predict which persons have which outcomes. If baselines existed for all variations of all conditions, then managing health could be improved by matching the measuring of individuals to their cohort in the population. The scale required for complete baselines involves effective National Surveys of Population Health (NSPH). Traditionally, these have been focused upon acute medicine, measuring people to contain the spread of epidemics. In recent decades, the focus has moved to chronic conditions as well, which require smaller measures over longer times. NSPH have long utilized quality of life questionnaires. Mobile Health Monitors, where computing technologies eliminate manual administration, provide richer data sets for health measurement. Older technologies of telephone interviews will be replaced by newer technologies of smartphone sensors to provide deeper individual measures at more frequent timings across larger-sized populations. Such continuous data can provide personal health records, supporting treatment guidelines specialized for population cohorts. Evidence-based medicine will become feasible by leveraging hundreds of millions of persons carrying mobile devices interacting with Internet-scale services for Big Data Analytics.

The French CONSTANCES population-based cohort: design, inclusion and follow-up

The CONSTANCES general-purpose cohort is intended to serve as an epidemiological research infrastructure accessible to the epidemiologic research community with a focus on occupational and social factors, and on chronic diseases and aging. CONSTANCES will also provide useful public health information to the public health authorities since it was designed as a large representative sample of the general French adult population. CONSTANCES is designed as a randomly selected representative sample of French adults aged 18–69 years at inception; 200,000 subjects will be included over a five-year period. At inclusion, the selected subjects are invited to complete questionnaires and to attend a Health Screening Center (HSC) for a comprehensive health examination. A biobank will be set up. The follow-up includes a yearly self-administered questionnaire, and a periodic visit to an HSC. Social and health data are collected from the French national databases. Data collected for participants include social and demographic characteristics, socioeconomic status, life events, behaviors, and occupational factors. The health data cover a wide spectrum: self-reported health scales, reported prevalent and incident diseases, long-term chronic diseases and hospitalizations, sick-leaves, handicaps, limitations, disabilities and injuries, healthcare utilization and services provided, and causes of death. To take into account non-participation at inclusion and attrition throughout the longitudinal follow-up, a cohort of non-participants was set up and will be followed through the same national databases as participants. Inclusion begun at the end of 2012 and more than 82,000 were already included by September 2015. A public call for nested research projects was launched.

Stigma and the addiction paradigm for obesity: lessons from 1950s America

AIMS

To discuss an historical episode in which obesity was conceptualized as an addictive disorder and declared to be a major epidemic in the early postwar United States. This history illuminates past consequences of framing obesity as an addiction in ways that may inform constructive policy responses today.

METHODS

Review of secondary and primary sources, including archival documents, relating to obesity in biomedical and popular thought of the 1940s and 1950s.

RESULTS

In the United States in the late 1940s and 1950s, new medical thinking about obesity reinterpreted overweight and obesity as chiefly the consequence of addiction (understood in the then dominant psychodynamic theory as a psychological defect, oral fixation). This new conception was rapidly taken up in popular discourse and clinical practice, with adverse effects through amplification of weight stigma. Further, in the conservative political context, the addiction concept contributed to an ineffective policy response to the alarming new epidemiological evidence about obesity's consequences. Despite a lack of evidence for efficacy of the intervention, public health efforts focused on correcting individual eating behaviour among obese people by encouraging self-help in lay groups modelled, in part, on Alcoholics Anonymous. Population-level intervention was neglected.

CONCLUSIONS

Current public health policy initiatives must be mindful of the risks of reframing obesity as an addiction. These include inadvertently reinforcing stigma, narrowing responses to those aiming to modify individual behaviour and biology and neglecting population policies aiming to reduce the consumption of energy-dense foods, as all occurred in the 1950s United States.

Integromic analysis of genetic variation and gene expression identifies networks for cardiovascular disease phenotypes

BACKGROUND

Cardiovascular disease (CVD) reflects a highly coordinated complex of traits. Although genome-wide association studies have reported numerous single nucleotide polymorphisms (SNPs) to be associated with CVD, the role of most of these variants in disease processes remains unknown.

METHODS AND RESULTS

We built a CVD network using 1512 SNPs associated with 21 CVD traits in genome-wide association studies (at P≤5×10(-8)) and cross-linked different traits by virtue of their shared SNP associations. We then explored whole blood gene expression in relation to these SNPs in 5257 participants in the Framingham Heart Study. At a false discovery rate <0.05, we identified 370 cis-expression quantitative trait loci (eQTLs; SNPs associated with altered expression of nearby genes) and 44 trans-eQTLs (SNPs associated with altered expression of remote genes). The eQTL network revealed 13 CVD-related modules. Searching for association of eQTL genes with CVD risk factors (lipids, blood pressure, fasting blood glucose, and body mass index) in the same individuals, we found examples in which the expression of eQTL genes was significantly associated with these CVD phenotypes. In addition, mediation tests suggested that a subset of SNPs previously associated with CVD phenotypes in genome-wide association studies may exert their function by altering expression of eQTL genes (eg, LDLR and PCSK7), which in turn may promote interindividual variation in phenotypes.

CONCLUSIONS

Using a network approach to analyze CVD traits, we identified complex networks of SNP-phenotype and SNP-transcript connections. Integrating the CVD network with phenotypic data, we identified biological pathways that may provide insights into potential drug targets for treatment or prevention of CVD.

Predicting return to work among sickness-certified patients in general practice: properties of two assessment tools

AIM

The purpose was to analyse the properties of two models for the assessment of return to work after sickness certification, a manual one based on clinical judgement including non-measurable information ('gut feeling'), and a computer-based one.

STUDY POPULATION

All subjects aged 18 to 63 years, sickness-certified at a primary health care centre in Sweden during 8 months (n = 943), and followed up for 3 years.

METHODS

Baseline information included age, sex, occupational status, sickness certification diagnosis, full-time or part-time current sick-leave, and sick-leave days during the past year. Follow-up information included first and last day of each occurring sick spell. In the manual model all subjects were classified, based on baseline information and gut feeling, into a high-risk (n = 447) or a low-risk group (n = 496) regarding not returning to work when the present certificate expired. It was evaluated with a Cox's analysis, including time and return to work as dependent variables and risk group assignment as the independent variable, while in the computer-based model the baseline variables were entered as independent variables.

RESULTS

Concordance between actual return to work and return to work predicted by the analysis model was 73%-76% during the first 28-180 days in the manual model, and approximately 10% units higher in the computer-based model. Based on the latter, three nomograms were constructed providing detailed information on the probability of return to work.

CONCLUSION

The computer-based model had a higher precision and gave more detailed information than the manual model.

Identifying the appropriate comparison group for HIV-infected individuals

PURPOSE OF REVIEW

HIV-infected individuals are living longer as a result of effective treatment. Age-related comorbidities now account for the majority of morbidity and mortality among treated HIV-infected adults. Previous findings regarding the age at, and risk of, these comorbidities have been mixed, sparking debate in the field. Discerning potential differences in the occurrence and burden of age-related comorbidities among treated HIV-infected adults as compared with uninfected adults of the same age requires careful selection of the appropriate uninfected comparison group.

RECENT FINDINGS

The validity of comparisons with HIV-uninfected populations is threatened when differences in demographic, clinical, and lifestyle characteristics between HIV-infected and uninfected adults are not considered. Identifying a pool of HIV-uninfected individuals from existing secondary data resources and employing selection methodologies may be a novel approach to reduce threats to internal validity. Issues related to identifying data sources, understanding inclusion criteria, determining measurement error, and threats to inference are discussed.

SUMMARY

The development of clinical interventions targeting age-related comorbidities will rely on deriving valid inferences from appropriate comparison groups. The use of secondary data resources and selection methodology to create the appropriate uninfected comparison group is an attractive approach in the setting of finite resources, but are not without limitations.

From administrative infrastructure to biomedical resource: Danish population registries, the "Scandinavian laboratory," and the "epidemiologist's dream"

Since the 1970s, Danish population registries were increasingly used for research purposes, in particular in the health sciences. Linked with a large number of disease registries, these data infrastructures became laboratories for the development of both information technology and epidemiological studies. Denmark's system of population registries had been centralized in 1924 and was further automated in the 1960s, with individual identification numbers (CPR-numbers) introduced in 1968. The ubiquitous presence of CPR-numbers in administrative routines and everyday lives created a continually growing data archive of the entire population. The resulting national-level database made possible unprecedented record linkage, a feature epidemiologists and biomedical scientists used as a resource for population health research. The specific assemblages that emerged with their practices of data mining were constitutive of registry-based epidemiology as a style of thought and of a distinct relationship between science, citizens, and the state that emerged as “Scandinavian.”

Defining an epidemic: the body mass index in British and US obesity research 1960-2000

Between the 1970s and the mid-1990s the body mass index (BMI) became the standard means of assessing obesity both in populations and in individuals, replacing previously diverse and contested definitions of excess body weight. This article draws on theoretical approaches from the sociology of standards and science and technology studies to describe the development of this important new standard and the ways in which its adoption facilitated the development of obesity science, that is, knowledge about the causes, health effects and treatments of excess body weight. Using an analysis of policy and healthcare literatures, I argue that the adoption of the BMI, along with associated standard cut-off points defining overweight and obesity, was crucial in the framing of obesity as an epidemic. This is because, I suggest, these measures enabled, firstly, the creation of large data sets tracking population-level changes in average body weight, and, secondly, the construction of visual representations of these changes. The production of these two new techniques of representation made it possible for researchers in this field, and others such as policymakers, to argue credibly that obesity should be described as an epidemic.

Legacy of the framingham heart study: rationale, design, initial findings, and implications

With the dramatic rise in coronary heart disease (CHD) during the first half of the 20th century, the newly formed National Heart Institute realized the significant gap in knowledge about the causes of CHD and embarked in 1947 on planning what was to become the renowned Framingham Heart Study. Dr. Thomas Royal Dawber's initial paper on the design of the project described studying up to 6,000 persons in a single geographic area and the formation of a technical advisory committee of 11 physicians in cardiology and public health to determine the hypotheses and protocol. A comprehensive physical examination and series of measurements and laboratory work were proposed and the initial examination was completed in 1952. The first paper describing 4 years of follow-up was published in 1957, and this was followed by a subsequent report in 1959 describing 6 years of follow-up. The first follow-up report described sex and age group differences in incidence of CHD and pointed out the noteworthy prominence of sudden cardiac death as the first manifestation of CHD and the initial observations regarding the significance of elevated blood pressure, cholesterol, and overweight in predicting future CHD. Importantly, the significance of a combination of risk factors for identifying those at highest risk was described as well as how the number of risk factors related to risk (the beginnings of what was decades later to become the famous risk scores from Framingham). Dr. William Kannel's 1961 publication, "Factors of Risk in the Development of Coronary Heart Disease," first highlighted the term risk factors, and it described how specific levels of cholesterol, blood pressure, as well as how electrocardiographic left ventricular hypertrophy predicted future CHD incidence. The standardized measurement of risk factors and follow-up in Framingham served as an important precedent for future observational studies designed and directed by what is now the National Heart, Lung, and Blood Institute, including the ARIC (Atherosclerosis Risk in Communities) study, the CARDIA (Coronary Artery Risk Development in Young Adults) study, the CHS (Cardiovascular Health Study), and the MESA (Multiethnic Study of Atherosclerosis). These studies and others continue the legacy that Framingham began more than 60 years ago into the investigation of the epidemiology of cardiovascular diseases.

Appropriating Risk Factors: The Reception of an American Approach to Chronic Disease in the two German States, c. 1950–1990

Risk factors have become a dominant approach to the aetiology of chronic disease worldwide. The concept emerged in the new field of chronic disease epidemiology in the United States in the 1950s, around near-iconic projects such as the Framingham Heart Study. In this article I examine how chronic disease epidemiology and the risk factor concept were adopted and adapted in the two German states. I draw on case studies that illuminate the characteristics of the different contexts and different take on traditions in social hygiene, social medicine and epidemiology. I also look at critics of the risk factor approach in East and West Germany, who viewed risk factors as intellectually dishonest and a new surveillance tool.

Gene expression analysis of whole blood, peripheral blood mononuclear cells, and lymphoblastoid cell lines from the Framingham Heart Study

Despite a growing number of reports of gene expression analysis from blood-derived RNA sources, there have been few systematic comparisons of various RNA sources in transcriptomic analysis or for biomarker discovery in the context of cardiovascular disease (CVD). As a pilot study of the Systems Approach to Biomarker Research (SABRe) in CVD Initiative, this investigation used Affymetrix Exon arrays to characterize gene expression of three blood-derived RNA sources: lymphoblastoid cell lines (LCL), whole blood using PAXgene tubes (PAX), and peripheral blood mononuclear cells (PBMC). Their performance was compared in relation to identifying transcript associations with sex and CVD risk factors, such as age, high-density lipoprotein, and smoking status, and the differential blood cell count. We also identified a set of exons that vary substantially between participants, but consistently in each RNA source. Such exons are thus stable phenotypes of the participant and may potentially become useful fingerprinting biomarkers. In agreement with previous studies, we found that each of the RNA sources is distinct. Unlike PAX and PBMC, LCL gene expression showed little association with the differential blood count. LCL, however, was able to detect two genes related to smoking status. PAX and PBMC identified Y-chromosome probe sets similarly and slightly better than LCL.

Epidemiology of critical care syndromes, organ failures, and life-support interventions in a suburban US community

BACKGROUND

ICU services represent a significant and increasing proportion of medical care. Population-based epidemiologic studies are essential to inform physicians and policymakers about current and future ICU demands. We aimed to determine the incidence of critical care syndromes, organ failures, and life-support interventions in a defined US suburban community with unrestricted access to critical care services.

METHODS

This population-based observational cohort from January 1 to December 31, 2006, in Olmsted County, Minnesota, included all consecutive critically ill adult residents admitted to the ICU. Main outcomes were incidence of critical care syndromes, life-support interventions, and organ failures as defined by standard criteria. Incidences are reported per 100,000 population (95% CIs) and were age adjusted to the 2006 US population.

RESULTS

A total of 1,707 ICU admissions were identified from 1,461 patients. Incidences of critical care syndromes were respiratory failure, 430 (390-470); acute kidney injury, 290 (257-323); severe sepsis, 286 (253-319); all-cause shock, 194 (167-221); acute lung injury, 86 (68-105); all-cause coma, 43 (30-55); and overt disseminated intravascular coagulation, 18 (10-26). Incidence of mechanical ventilation was invasive, 310 (276-344); noninvasive, 180 (154-206); vasopressors and inotropes, 183(155-208). Renal replacement therapy incidence was 96 (77-116). Of the cohort, 1,330 patients (91%) survived to hospital discharge. Short- and long-term survival decreased by the number of failing organs.

CONCLUSIONS

In a suburban US community with high access to critical care services, cumulative incidences of critical care syndromes and life-support interventions were higher than previously reported. The results of this study have important implications for future planning of critical care delivery.

Balcova heart study: rationale and methodology of the Turkish cohort

OBJECTIVES

Turkey is facing increasing rates of cardiovascular disease (CVD). The study is designed to meet the growing need to obtain information about the recent status and trends of CVD risk factors and their impact on mortality.

METHODS

Balcova heart study (BHS) is a prospective cohort study, focusing on reducing the CVD risk factors of people over 30 years old living in Balcova District, Izmir, Turkey. Information about risk factors, anthropometric and biochemical measurements was collected in community centers. Interventions were planned, based on the 10-year coronary heart disease (CHD) risk and lifestyle characteristics with the collaboration of university and municipality.

RESULTS

Mean age of the 16,080 participants was 52 years. The percentage of current smoking was 41.6 in men and 31.1 in women. One-third of the men were physically inactive. Hypertension was reported as 25% in men and 33% in women.

CONCLUSIONS

The project is unique for being the first community-based cohort on CVD risk factors in a Turkish setting. This project will have a valuable contribution on not only determining CVD risks, but also incorporating interventions for prevention.

'Population laboratories' or 'laboratory populations'? Making sense of the Baltimore Longitudinal Study of Aging, 1965-1987

Interest among historians, philosophers and sociologists of science in population-based biomedical research has focused on the randomised controlled trial to the detriment of the longitudinal study, the temporally extended, serial observation of individuals residing in the same community. This is perhaps because the longitudinal study is regarded as having played a secondary role in the debates about the validity of populations-based approaches that helped to establish epidemiology as one of the constitutive disciplines of contemporary biomedicine. Drawing on archival data and publications relating to the Baltimore Longitudinal Study of Aging, we argue however that the historical development of the longitudinal study is richer and more significant than has been appreciated. We argue that this history is shaped by the tension between two sets of epistemic practices, devices and norms. On the one side there were those who emphasised randomisation and sampling to evidence claims about, and justify policies with respect to, the aetiology of disease. On the other side there were those who evoked the technical repertoire of physiological research, especially the notion of the 'model organism', to argue for a different integration of the individual in modern society.

The CONSTANCES cohort: an open epidemiological laboratory

Background

Prospective cohorts represent an essential design for epidemiological studies and allow for the study of the combined effects of lifestyle, environment, genetic predisposition, and other risk factors on a large variety of disease endpoints. The CONSTANCES cohort is intended to provide public health information and to serve as an "open epidemiologic laboratory" accessible to the epidemiologic research community. Although designed as a "general-purpose" cohort with very broad coverage, it will particularly focus on occupational and social determinants of health, and on aging.

Methods/Design

The CONSTANCES cohort is designed as a randomly selected representative sample of French adults aged 18-69 years at inception; 200,000 subjects will be included over a five-year period. At inclusion, the selected subjects will be invited to fill a questionnaire and to attend a Health Screening Center (HSC) for a comprehensive health examination: weight, height, blood pressure, electrocardiogram, vision, auditory, spirometry, and biological parameters; for those aged 45 years and older, a specific work-up of functional, physical, and cognitive capacities will be performed. A biobank will be set up. The follow-up includes a yearly self-administered questionnaire, and a periodic visit to an HSC. Social and work-related events and health data will be collected from the French national retirement, health and death databases. The data that will be collected include social and demographic characteristics, socioeconomic status, life events, behaviors, and occupational factors. The health data will cover a wide spectrum: self-reported health scales, reported prevalent and incident diseases, long-term chronic diseases and hospitalizations, sick-leaves, handicaps, limitations, disabilities and injuries, healthcare utilization and services provided, and causes of death.

To take into account non-participation at inclusion and attrition throughout the longitudinal follow-up, a cohort of non-participants will be set up and followed through the same national databases as participants.

A field-pilot was performed in 2010 in seven HSCs, which included about 3,500 subjects; it showed a satisfactory structure of the sample and a good validity of the collected data.

Discussion

The constitution of the full eligible sample is planned during the last trimester of 2010, and the cohort will be launched at the beginning of 2011.

Framingham Heart Study: the first 20 years

The Framingham Heart Study remains the most famous and influential investigation in cardiovascular disease epidemiology. To generations of epidemiologists, it is a model for the cohort design. Here we revisit the origins of the Framingham Study before it became an accomplished and famous investigation whose existence and success are taken for granted. When in 1947 the Public Health Service initiated the study, knowledge of the distribution and determinants of coronary heart disease was sparse. Epidemiology was primarily focused on infectious disorders. Framingham's pioneers struggled to invent an appropriate epidemiological approach to this chronic disease and to establish support for a new kind of research within a community. Thereafter they had to convince skeptical medical professionals that the results of epidemiological investigations of heart disease were applicable to their clinical practices.

Mining data, gathering variables and recombining information: the flexible architecture of epidemiological studies

Since the second half of the twentieth century, biomedical research has made increasing use of epidemiological methods to establish empirical evidence on a population level. This paper is about practices with data in epidemiological research, based on a case study in Denmark. I propose an epistemology of record linkage that invites exploration of epidemiological studies as heterogeneous assemblages. Focusing on data collecting, sampling and linkage, I examine how data organisation and processing become productive beyond the context of their collection. The case study looks at how a local population database established in 1976 to investigate possibilities for the prevention of cardiovascular disease is used thirty years later to test hypotheses on the aetiology of breast cancer. For two breast cancer investigations based on the same core data set, I follow the underlying record linkage practice and describe how research objects such as molecular markers become relevant with respect to public health through information networking. Epidemiological association studies function as tools that performatively enrol different contexts into statistical risk estimation, thereby configuring options for research as well as for clinical testing and public health policy.

Epidemiological sociology and the social shaping of population health

When biomedical knowledge and technology create the capacity for humans to avoid disease and circumvent early death, sociological factors become more, not less important for population health. The transformation of disease causation from cruel fate, accident, and bad luck to circumstances that are under some degree of human control facilitates a powerful social shaping of disease and death. When humans have control, it is their policies, their knowledge, and their behaviors that shape the consequences of biomedical accomplishments, and thereby extant patterns of disease and death. I propose a "social shaping approach" that can frame our understanding of these processes and allow us to take action to optimize population health. Support for this approach is garnered from evidence of dramatic improvements in population health and in the uneven distribution of those improvements across persons, places, and times. Health improvements suggest that humans have gained control of disease whereas the uneven and very slow spread of such improvements underscores the critical importance of social factors. But the evidence presented represents a stick figure at best, one that needs to be filled in by a well-supported "epidemiological sociology" that uses a wide range of sociological concepts and theories to elucidate the social shaping of disease and death. Absent a robust societal investment in epidemiological sociology, population health will reside below its optimal level and the maldistribution of health-enhancing innovations will continue to create health disparities.

Systems Epidemiology in Cancer

Prospective studies in cancer epidemiology have conserved their study design over the last decades. In this context, current epidemiologic studies investigating gene-environment interactions are based on biobank for the analysis of genetic variation and biomarkers, using notified cancer as outcome. These studies result from the use of high-throughput technologies rather than from the development of novel design strategies. In this article, we propose the globolomic design to run integrated analyses of cancer risk covering the major -omics in blood and tumor tissue. We defined this design as an extension of the existing prospective design by collecting tissue and blood samples at time of diagnosis, including biological material suitable for transcriptome analysis. The globolomic design opens up for several new analytic strategies and, where gene expression profiles could be used to verify mechanistic information from experimental biology, adds a new dimension to causality in epidemiology. This could improve, for example, the interpretation of risk estimates related to single nucleotide polymorphisms in gene-environment studies by changing the criterion of biological plausibility from a subjective discussion of in vitro information to observational data of human in vivo gene expression. This ambitious design should consider the complexity of the multistage carcinogenic process, the latency time, and the changing lifestyle of the cohort members. This design could open the new research discipline of systems epidemiology, defined in this article as a counterpart to systems biology. Systems epidemiology with a focus on gene functions challenges the current concept of biobanking, which focuses mainly on DNA analyses. (Cancer Epidemiol Biomarkers Prev 2008;17(11):2954–7)

"Coming together, keeping together, working together": interdisciplinary to transdisciplinary research and nursing

To enhance clinical science and hasten the translation of research to practice so as to ultimately improve health, an increasing emphasis is being placed on transdisciplinary research. The purpose of this article is to describe the development of transdisciplinary clinical research in nursing, the current state of the science, potential threats to the discipline, and the promise of transdisciplinary research for nursing and for the health of the public. To successfully engage in transdisciplinary research, nurse scientists can use multiple strategies, including continuing to prepare researchers in rigorous pre-doctoral and postdoctoral training programs.

[Cohort study and multivariate analysis: an epistemological and historical analysis of the Framingham heart study]

BACKGROUND

Begun in 1947 and still ongoing, the epidemiological study of heart disease known as the Framingham study was one of the first prospective studies based on a large cohort and has rapidly been considered as the prototype and model for the cohort study. Nevertheless, an examination of its history reveals that the protocol does not at all correspond to today's standards for this type of study. How, then, can we account for the remarkable reputation of this study?

METHODS

This paper consists in an epistemological and historical analysis of the Framingham study that provides some of the answers to this question. In my treatment of the study's methodology, I focus on the issue of how the study population was constituted, and the manner in which the multiple factor analyses were conducted, two issues that are now central to cohort studies and more generally to analytic epidemiology.

RESULTS

I show how the study population of Framingham and its long-term follow-up have contributed significantly to the interpretation of the cohort as a sort of "population-laboratory". The data generated by this study, which have been very widely used by epidemiologists and other researchers, are unparalleled in terms of the amount of detailed clinical information available for such a long follow-up period. Furthermore, multivariate statistical modelling, which has become a standard statistical tool for clinical as well as epidemiological studies was introduced in the context of this study to improve the identification of significant factors in the simultaneous analysis of multiple correlations. Multivariate analysis has since proved crucial in shaping the epidemiological concept of "risk factor" and in analysing multifactorial diseases. Indeed, I suggest that the modern idea of multifactorial diseases depends on the adaptation of this statistical method.

CONCLUSION

Thus, the Framingham study played a leading role not only in remodelling epidemiology after Second World War, in particular because of its contribution to the establishment of the cohort study as a standard method of investigation in etiological research, but also in constituting the "risk factor approach" to disease.