Data sharing: What about epidemiological cohorts?

General-purpose population-based cohorts can be powerful scientific platforms. The Gazel Cohort Study, a French cohort of 20,000 adults followed-up since more than 20 years, was designed as an open epidemiologic laboratory, hosting more than 40 nested research projects from French and international teams.
Formal rules were elaborated to define the way that the Gazel database can be accessed.
One of the main problems faced by the Gazel team members is scientific recognition of their work, as the large majority of the publications come from external research groups

OA-SLAM: Leveraging Objects for Camera Relocalization in Visual SLAM

In this work, we explore the use of objects in Simultaneous Localization and Mapping in unseen worlds and propose an object-aided system (OA-SLAM). More precisely, we show that, compared to low-level points, the major benefit of objects lies in their higher-level semantic and discriminating power. Points, on the contrary, have a better spatial localization accuracy than the generic coarse models used to represent objects (cuboid or ellipsoid). We show that combining points and objects is of great interest to address the problem of camera pose recovery. Our main contributions are: (1) we improve the relocalization ability of a SLAM system using high-level object landmarks; (2) we build an automatic system, capable of identifying, tracking and reconstructing objects with 3D ellipsoids; (3) we show that object-based localization can be used to reinitialize or resume camera tracking. Our fully automatic system allows on-the-fly object mapping and enhanced pose tracking recovery, which we think, can significantly benefit to the AR community. Our experiments show that the camera can be relocalized from viewpoints where classical methods fail. We demonstrate that this localization allows a SLAM system to continue working despite a tracking loss, which can happen frequently with an uninitiated user. Our code and test data are released at gitlab.inria.fr/tangram/oa-slam.Comment: ISMAR 202

The CONSTANCES cohort, an epidemiological research infrastructure. Methods and results of the pilot phase

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 epidemiological research infrastructure 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 chronic diseases and aging. Methods: the CON STANC ES 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 are 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 is 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 are collected from the French national retirement, health and death databases. The data 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. Results: 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. Conclusions: the constitution of the full eligible sample begun in 2012 and the cohort will be completed by the end of 2017. A public call for ancillary research projects will be launched in 2014

The Impact of Stressful Life Events on Excessive Alcohol Consumption in the French Population: Findings from the GAZEL Cohort Study

Background: Major life changes may play a causative role in health through lifestyle factors, such as alcohol. The objective was to examine the impact of stressful life events on heavy alcohol consumption among French adults. Methods: Trajectories of excessive alcohol consumption in 20,625 employees of the French national gas and electricity company for up to 5 years before and 5 years after an event, with annual measurements from 1992. We used repeated measures analysis of time series data indexed to events, employing generalized estimating equations. Results: For women, excessive alcohol use increased before important purchase (p = 0.021), children leaving home (p<0.001), and death of loved ones (p = 0.03), and decreased before widowhood (p = 0.015); in the year straddling the event, increased consumption was observed for important purchase (p = 0.018) and retirement (p = 0.002); at the time of the event, consumption decreased for marriage (p = 0.002), divorce, widowhood, and death of loved one (all p<0.001), and increased for retirement (p = 0.035). For men, heavy alcohol consumption increased in the years up to and surrounding the death of loved ones, retirement, and important purchase (all p<0.001), and decreased after (all p<0.001, except death of loved one: p = 0.006); at the time of the event, consumption decreased for all events except for children leaving home and retirement, where we observed an increase (all p<0.001). For women and men, heavy alcohol consumption decreased prior to marriage and divorce and increased after (all p<0.001, except for women and marriage: p = 0.01). Conclusion: Stressful life events promote healthy and unhealthy alcohol consumption. Certain events impact alcohol intake temporarily while others have longer-term implications. Research should disentangle women's and men's distinct perceptions of events over time

Intergenerational socioeconomic mobility and adult depression:the CONSTANCES study

Socioeconomic mobility from childhood onwards may predict depression risk in adulthood. Using data from the nationally representative CONSTANCES study in France (2012-2014, n=67,057), we assessed the relationship between intergenerational socioeconomic mobility and adult depression (Center for Epidemiological Studies-Depression scale, &gt;=16 in men, &gt;=20 in women) and antidepressant use. Socioeconomic position was ascertained by occupational grade (childhood: maternal and paternal measures prior to age 15 years combined; adult: participant own). Data were analyzed using logistic regression models adjusted for sociodemographic characteristics, parental history of psychiatric disorders and suicide, health behaviors and chronic health problems. Compared to participants who had persistently high socioeconomic circumstances, those who experienced other socioeconomic trajectories had elevated levels of depression (multivariate Odds Ratios: upward mobility: 1.21, intermediate socioeconomic position: 1.28, downward mobility: 1.66, persistently low socioeconomic position: 1.82). Downward mobility and persistently low socioeconomic position were also associated with elevated odds of antidepressant use (multivariate Odds Ratios: 1.24 and 1.36 respectively). In supplementary analyses, socioeconomic mobility was more strongly associated with depression in women than in men and in younger participants (18-29 years) than other age groups. Factors that contribute to depression risk and socioeconomic inequalities in this area appear at play already in childhood; this should be acknowledged by clinicians and policymakers

3D-Aware Ellipse Prediction for Object-Based Camera Pose Estimation

International audienceIn this paper, we propose a method for coarse camera pose computation which is robust to viewing conditions and does not require a detailed model of the scene. This method meets the growing need of easy deployment of robotics or augmented reality applications in any environments, especially those for which no accurate 3D model nor huge amount of ground truth data are available. It exploits the ability of deep learning techniques to reliably detect objects regardless of viewing conditions. Previous works have also shown that abstracting the geometry of a scene of objects by an ellipsoid cloud allows to compute the camera pose accurately enough for various application needs. Though promising, these approaches use the ellipses fitted to the detection bounding boxes as an approximation of the im-aged objects. In this paper, we go one step further and propose a learning-based method which detects improved elliptic approximations of objects which are coherent with the 3D ellipsoid in terms of perspective projection. Experiments prove that the accuracy of the computed pose significantly increases thanks to our method and is more robust to the variability of the boundaries of the detection boxes. This is achieved with very little effort in terms of training data acquisition-a few hundred calibrated images of which only three need manual object annotation. Code and models are released at https://github.com/zinsmatt/3D-Aware-Ellipses-for-Visual-Localization

Does Obesity Modify the Relationship between Exposure to Occupational Factors and Musculoskeletal Pain in Men? Results from the GAZEL Cohort Study

Objective: To analyze relationships between physical occupational exposures, post-retirement shoulder/knee pain, and obesity. Methods: 9 415 male participants (aged 63–73 in 2012) from the French GAZEL cohort answered self-administered questionnaires in 2006 and 2012. Occupational exposures retrospectively assessed in 2006 included arm elevation and squatting (never, <10 years, ≥10 years). “Severe” shoulder and knee pain were defined as ≥5 on an 8-point scale. BMI was self-reported. Results: Mean BMI was 26.59 kg/m2 +/−3.5 in 2012. Long-term occupational exposure to arm elevation and squatting predicted severe shoulder and knee pain after retirement. Obesity (BMI≥30 kg/m2) was a risk factor for severe shoulder pain (adjusted OR 1.28; 95% CI 1.03, 1.90). Overweight (adjusted OR 1.71; 1.28,2.29) and obesity (adjusted OR 3.21; 1.90,5.41) were risk factors for severe knee pain. In stratified models, associations between long-term squatting and severe knee pain varied by BMI. Conclusion: Obesity plays a role in relationships between occupational exposures and musculoskeletal pain. Further prospective studies should use BMI in analyses of musculoskeletal pain and occupational factors, and continue to clarify this relationship

Bioresource from the French Gazel Cohort Study

The GAZEL Cohort Study set up in 1989 is a general-purpose epidemiologic cohort. At inception in 1989, the cohort included 20,625 volunteers then aged from 35-50 (women; n= 5,614) or 40-50 (men; n= 15,011). The data collected routinely come from different sources, mainly annual self-administered questionnaires, socioeconomic and health administrative data, health examinations, and causes of death. The epidemiologic database is maintained and stored by our group in our own facilities; the biobank is stored in the “Centre de ressources biologiques”, in Dijon, France. Today, more than 50 epidemiological projects on diversified themes have been set up in the GAZEL Cohort Study by some 30 French and foreign teams.</p

Long working hours, anthropometry, lung function, blood pressure and blood-based biomarkers : cross-sectional findings from the CONSTANCES study

Background Although long working hours have been shown to be associated with the onset of cardiometabolic diseases, the clinical risk factor profile associated with long working hours remains unclear. We compared the clinical risk profile between people who worked long hours and those who reported being never exposed to long hours. Methods A cross-sectional study in 22 health screening centres in France was based on a random population-based sample of 75 709 participants aged 18-69 at study inception in 2012-2016 (the CONSTANCES study). The data included survey responses on working hours (never, former or current exposure to long working hours), covariates and standardised biomedical examinations including anthropometry, lung function, blood pressure and standard blood-based biomarkers. Results Among men, long working hours were associated with higher anthropometric markers (Body Mass Index, waist circumference and waist:hip ratio), adverse lipid levels, higher glucose, creatinine, white blood cells and higher alanine transaminase (adjusted mean differences in the standardised scale between the exposed and unexposed 0.02-0.12). The largest differences were found for Body Mass Index and waist circumference. A dose-response pattern with increasing years of working long hours was found for anthropometric markers, total cholesterol, glucose and gamma-glutamyltransferase. Among women, long working hours were associated with Body Mass Index and white blood cells. Conclusion In this study, men who worked long hours had slightly worse cardiometabolic and inflammatory profile than those who did not work long hours, especially with regard to anthropometric markers. In women, the corresponding associations were weak or absent.Peer reviewe

Usefulness of a single-item measure of depression to predict mortality: the GAZEL prospective cohort study.: single-item of depression and mortality

International audienceBACKGROUND: It remains unknown whether short measures of depression perform as well as long measures in predicting adverse outcomes such as mortality. The present study aims to examine the predictive value of a single-item measure of depression for mortality. METHODS: A total of 14,185 participants of the GAZEL cohort completed the 20-item Center-for-Epidemiologic-Studies-Depression (CES-D) scale in 1996. One of these items (I felt depressed) was used as a single-item measure of depression. All-cause mortality data were available until 30 September 2009, a mean follow-up period of 12.7 years with a total of 650 deaths. RESULTS: In Cox regression model adjusted for baseline socio-demographic characteristics, a one-unit increase in the single-item score (range 0-3) was associated with a 25% higher risk of all-cause mortality (95% CI: 13-37%, P<0.001). Further adjustment for health-related behaviours and physical chronic diseases reduced this risk by 36% and 8%, respectively. After adjustment for all these variables, every one-unit increase in the single-item score predicted a 15% increased risk of death (95% CI: 5-27%, P<0.01). There is also an evidence of a dose-reponse relationship between reponse scores on the single-item measure of depression and mortality. CONCLUSION: This study shows that a single-item measure of depression is associated with an increased risk of death. Given its simplicity and ease of administration, a very simple single-item measure of depression might be useful for identifying middle-aged adults at risk for elevated depressive symptoms in large epidemiological studies and clinical settings