Affective responses to sweet products and sweet solution in British and Finnish adults

Peer reviewe

Genetic causal beliefs about morbidity: associations with health behaviors and health outcome beliefs about behavior changes between 1982–2002 in the Finnish population.

Background: The role and meaning of genetic information has grown considerably in the recent decades. We examined changes in causal beliefs about morbidity as well as the associations between causal beliefs, health behaviors and obesity, and health outcome beliefs from 1982 to 2002. Methods: In five population-based risk-factor surveys (the FINRISK Studies) of individuals aged 25 to 64 years conducted from 1982 to 2002 (n = 37,503), respondents chose the most important cause of morbidity from a list of ten alternatives. Health outcome beliefs were assessed with two items. Physical inactivity and smoking status were based on self-reports and obesity was based on measured height and weight. Results: The prevalence of those who endorse genetic factors as the most important cause of morbidity increased from 4% in 1982 to 10% in 1992 and remained at that level until 2002. During the study period, lack of exercise and overweight increased, whereas inappropriate diet and stress diminished as causal beliefs about morbidity. Smokers and physically inactive were more likely to endorse genetic than behavioral causes of morbidity, whereas obese respondents were more likely to choose overweight over genetic causes of morbidity. Those who endorse genetic factors as the most important cause had more pessimistic outcome beliefs about health behavior changes, but these outcome beliefs became more positive in all causal belief groups during the study period. Conclusion: Despite increased public discussion of genomics, the relative proportion of those who endorse genetic factors as the most important cause of morbidity has remained low. However, within this group beliefs about benefits of health behavior changes have become more positive. This could indicate that increase in genomic health information does not lead to more negative appraisals of efficacy of lifestyle changes.Peer reviewe

Editorial : Can population health be personalized? Estonia and Finland as examples

Non peer reviewe

Psychosocial Effects of Receiving Genome-Wide Polygenic Risk Information Concerning Type 2 Diabetes and Coronary Heart Disease : A Randomized Controlled Trial

Receiving polygenic risk estimates of future disease through health care or direct-to-consumer companies is expected to become more common in the coming decades. However, only a limited number of studies have examined if such estimates might evoke an adverse psychosocial reaction in receivers. The present study utilized data from a sub-section of a personalized medicine project (the P5 study) that combines genomic and traditional health data to evaluate participants' risk for certain common diseases. We investigated how communication of future disease risk estimates related to type 2 diabetes and coronary heart disease influenced respondents' risk perception, self-efficacy, disease-related worry, and other emotions. A randomized controlled trial was conducted, where the experimental group (n = 714) received risk estimates based on traditional and polygenic risk factors and the control group (n = 649) based solely on traditional risk factors. On average, higher disease risk was associated with higher perceived risk (ps, 0.06).Peer reviewe

Reaching for Precision Healthcare in Finland via Use of Genomic Data

Concerns over future healthcare capacity along with continuing demands for sustainability call for novel solutions to improve citizens' health and wellbeing through effective prevention and improved diagnosis and treatment. Part of the solution to tackle the challenge could be making the most of the exploitation of genomic data in personalized risk assessment, creating new opportunities for data-driven precision prevention and public health. Presently, the utilization of genomic data in the Finnish healthcare system is limited to a few medical specialty areas. To successfully extend the use of genomic information in everyday healthcare, evidence-based and feasible strategies are needed. The national actions that Finland is taking towards this goal are 1) providing scientific evidence for the utility of genomic information for healthcare purposes; 2) evaluating the potential health-economic impact of implementing precision healthcare in Finland; 3) developing a relevant legal framework and infrastructures for the utilization of genomic information; 4) building a national multidisciplinary expert network bringing together relevant professionals and initiatives to achieve consensus among the different stakeholders on specific issues vital for translating genomic data into precision healthcare; 5) building competence and genomic literacy skills among various target groups; and 6) public engagement (informing and educating the public). Taken together, these actions will enable building a roadmap towards the expedient application of genomic data in Finnish healthcare and promoting the health of our citizens.Peer reviewe

Role of Academic Biobanks in Public-Private Partnerships in the European Biobanking and BioMolecular Resources Research Infrastructure Community

Public-private partnerships (PPP) are an efficient means to advance scientific discoveries and boost the medical innovations needed to improve precision medicine. The increasing number and novel nature of such collaborations is keeping the biomedical field in a constant flux. Here we provide an update on PPP development involving academic biobanks in the BBMRI community (the European Biobanking and BioMolecular Resources Research Infrastructure) and report the views on PPP of 20 key players from this field. The interviewed academic representants broadly show interest for their institution to establish PPP and initiate or partner with BBMRI expert centers. The results indicate that PPP has gained foothold in this area of biomedical research, with great promise to facilitate access to samples and data and to improve data interoperability and reproducibility.Peer reviewe

Family history and perceived risk of diabetes, cardiovascular disease, cancer, and depression

Background: Family history is a useful and inexpensive tool to assess risks of multifactorial diseases. Family history enables individualized disease prevention, but its effects on perceived risks of various diseases need to be understood in more detail. We examined how family history relates to perceived risk of diabetes mellitus, cardiovascular disease (CVD), cancer, and depression, and whether these associations are independent of or moderated by sociodemographic factors, health behavior/weight status (smoking, alcohol consumption, physical activity, BMI [kg/m²]), or depressive symptoms. Methods: Participants were Finnish 25−74-year-olds (N=6258) from a population-based FINRISK 2007 study. Perceived absolute lifetime risks (1–5) and first-degree family history of CVD, diabetes, cancer and depression, and health behaviors were self-reported. Weight and height were measured in a health examination. Results: Family history was most prevalent for cancer (36.7 %), least for depression (19.6 %). Perceived risk mean was highest for CVD (2.8), lowest for depression (2.0). Association between family history and perceived risk was strongest for diabetes (β=0.34, P<0.001), weakest for depression (β=0.19, P<0.001). Adjusting for sociodemographics, health behavior, and depressive symptoms did not change these associations. The association between family history and perceived risk tended to be stronger among younger than among older adults, but similar regardless of health behaviors or depressive symptoms. Discussion: Association between family history and perceived risk varies across diseases. People’s current understandings on heritability need to be acknowledged in risk communication practices. Future research should seek to identify effective strategies to combine familial and genetic risk communication in disease prevention.Peer reviewe