Measuring the predictability of life outcomes with a scientific mass collaboration.

How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences

Self-reported infections in the German National Cohort (GNC) in the context of the current research landscape.

Background: Infectious diseases continue to play an important role for disease perception, health-economic considerations and public health in Germany. In recent years, infectious diseases have been linked to the development of non-communicable diseases. Analyses of the German National Cohort (GNC) may provide deeper insights into this issue and pave the way for new targeted approaches in disease prevention. Objectives: The aim was to describe the tools used to assess infectious diseases and to present initial data on infectious disease frequencies, as well as to relate the GNC assessment tools to data collection methods in other studies in Germany. Methods: As part of the baseline examination, questions regarding infectious diseases were administered using both an interview and a self-administered touchscreen questionnaire. Data from the initial 101,787 GNC participants were analysed. Results: In the interview, 0.2% (HIV/AIDS) to 8.6% (shingles) of respondents reported ever having a medical diagnosis of shingles, postherpetic neuralgia (in cases where shingles was reported), hepatitis B/C, HIV/AIDS, tuberculosis or sepsis if treated in hospital. In the questionnaire, 12% (cystitis) to 81% (upper respiratory tract infections) of respondents reported having experienced at least one occurrence of upper or lower respiratory tract infections, gastrointestinal infections, cystitis or fever within the past 12 months. Outlook: The cross-sectional analyses of data and tools presented here – for example on determinants of susceptibility to self-reported infections – can be anticipated from the year 2021 onward. Beyond that, more extensive research into infectious disease epidemiology will follow, particularly once analyses of GNC biological materials have been performed

Measuring the predictability of life outcomes with a scientific mass collaboration.

How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences

Framework and baseline examination of the German National Cohort (NAKO).

The German National Cohort (NAKO) is a multidisciplinary, population-based prospective cohort study that aims to investigate the causes of widespread diseases, identify risk factors and improve early detection and prevention of disease. Specifically, NAKO is designed to identify novel and better characterize established risk and protection factors for the development of cardiovascular diseases, cancer, diabetes, neurodegenerative and psychiatric diseases, musculoskeletal diseases, respiratory and infectious diseases in a random sample of the general population. Between 2014 and 2019, a total of 205,415 men and women aged 19-74 years were recruited and examined in 18 study centres in Germany. The baseline assessment included a face-to-face interview, self-administered questionnaires and a wide range of biomedical examinations. Biomaterials were collected from all participants including serum, EDTA plasma, buffy coats, RNA and erythrocytes, urine, saliva, nasal swabs and stool. In 56,971 participants, an intensified examination programme was implemented. Whole-body 3T magnetic resonance imaging was performed in 30,861 participants on dedicated scanners. NAKO collects follow-up information on incident diseases through a combination of active follow-up using self-report via written questionnaires at 2-3 year intervals and passive follow-up via record linkages. All study participants are invited for re-examinations at the study centres in 4-5 year intervals. Thereby, longitudinal information on changes in risk factor profiles and in vascular, cardiac, metabolic, neurocognitive, pulmonary and sensory function is collected. NAKO is a major resource for population-based epidemiology to identify new and tailored strategies for early detection, prediction, prevention and treatment of major diseases for the next 30 years