The response to receiving phenotypic and genetic coronary heart disease risk scores and lifestyle advice – a qualitative study

BACKGROUND: Individuals routinely receive information about their risk of coronary heart disease (CHD) based on traditional risk factors as part of their primary care. We are also able to calculate individual's risk of CHD based on their genetic information and at present genetic testing for common diseases is available to the public. Due to the limitations in previous studies further understanding is needed about the impact of the risk information on individual's well-being and health-behaviour. We aimed to explore the short term response to receiving different forms of CHD risk information and lifestyle advice for risk reduction. METHODS: We conducted fourty-one face-to-face interviews and two focus groups across England with participants from the INFORM trial who received a combination of individualised phenotypic and genotypic CHD risk scores and web-based lifestyle advice. Risk scores were presented in different formats, e.g. absolute 10 year risk was presented as a thermometer and expressed as a percentage, natural frequency and 'heart age'. Interviews and focus groups explored participants' understanding and reaction to the risk scores and attempts to change lifestyle during the intervention. We tape-recorded and transcribed the interviews and focus groups and analysed them using thematic analysis. RESULTS: Three main themes were identified: limitations of risk scores to generate concern about CHD risk; the advantages of the 'heart age' format of risk score presentation in communicating a message of sub-optimal lifestyle; and intentions and attempts to make moderate lifestyle changes which were prompted by the web-based lifestyle advice. CONCLUSIONS: There are a number of limitations to the use of risk scores to communicate a message about the need for a lifestyle change. Of the formats used, the 'heart age', if noticed, appears to convey the most powerful message about how far from optimal risk an individual person is. An interactive, user friendly, goal setting based lifestyle website can act as a trigger to initiate moderate lifestyle changes, regardless of concerns about risk scores.INFORM is funded by European Commission Framework 7 EPIC-CVD Grant agreement no: 279233. NHS Blood and Transplant funded the INTERVAL trial. DNA extraction and genotyping in INTERVAL/INFORM was funded by the UK National Institute of Health Research. The coordinating team for INTERVAL/INFORM at the Cardiovascular Epidemiology Unit of the University of Cambridge was supported by core funding from: UK Medical Research Council (G0800270), British Heart Foundation (SP/09/002), British Heart Foundation Cambridge Cardiovascular Centre of Excellence, and UK National Institute for Health Research Cambridge Biomedical Research Centre

Dementia primary prevention policies and strategies and their local implementation: a scoping review using England as a case study

This is the author accepted manuscript. The final version is available from IOS Press via the DOI in this record.Background: Understanding policy context and how policy is implemented at the local and clinical level is an important precursor to developing preventive strategies focusing on dementia risk reduction in primary healthcare settings. Objective: Using England as a case study, we review policies and strategies relevant to dementia prevention from the national to local level and how these are translated into primary healthcare services. Methods: We conducted a scoping review covering: (a) identification of national, regional and local policies and strategies that include dementia prevention; (b) identification of national guidelines for implementing dementia prevention at the clinical level; and (c) evaluation of the implementation of these at the clinical level. Results: Dementia prevention is addressed in national policy, and this filters through to regional and local levels. Focus on dementia prevention is limited and variable. Reference to modifiable risk factors is associated with other non-communicable diseases, placing less emphasis on factors more dementia specific. Evidence of implementation of dementia prevention policies at the clinical level is limited and inconsistent. Available evidence suggests messages about dementia prevention may best be delivered through primary healthcare services such as the National Health Service (NHS) Health Check. Conclusion: The limitations identified in this review could be addressed through development of a national policy focused specifically on dementia prevention. This could provide a platform for increasing knowledge and understanding among the general population and healthcare professionals. It would be important for such a policy to cover the full range of modifiable risk factors relevant to dementia.This work was supported by the following grant: Centre for Research Excellence in Promoting Cognitive Health and Preventing Cognitive Decline with Chief Investigator Professor Kaarin Anstey. Funder’s number: APP 1100579

The associations between the response efficacy and objective and subjective change in physical activity and diet in the Information and Risk Modification trial.

OBJECTIVES: Many health promotion campaigns and interventions focussing on improving health-related behaviours have been based on targeting response efficacy. This is based on the assumption that response efficacy is an important modifiable determinant of behaviour change. This study aimed to quantify the association between response efficacy and objective and subjective measures of physical activity and diet. STUDY DESIGN: Prospective cohort analysis of data from a randomised controlled trial. METHODS: A total of 953 participants were assessed for response efficacy at baseline and 12 weeks following randomisation to interventions to increase physical activity and improve diet. Subjective measures were collected via a self-report questionnaire that included two questions used to derive the Cambridge Index of physical activity and questions about daily or weekly fruit and vegetable, whole grain, meat and fish intake, based on the dietary guidelines to lower cardiovascular risk. Objective measures were quantified using accelerometers and plasma carotenoids. RESULTS: The mean change in response efficacy for physical activity was +0.5 (standard deviation [SD] 2.0) and for diet was +0.5 (SD 2.1).There were no clinically or statistically significant associations between baseline or change in response efficacy and objective and subjective measures of physical activity or objective measures of diet. There was a small statistically significant association between baseline response efficacy and change in self-reported wholegrain consumption, but this is unlikely to be clinically significant. CONCLUSIONS: Response efficacy is not a fundamental determinant of diet and physical activity and should not be the main focus of interventions targeting these behaviours

Associations of awareness of age-related change with emotional and physical well-being: a systematic review and meta-analysis

This is the final version. Available on open access from OUP via the DOI in this recordBACKGROUND AND OBJECTIVES: This systematic review aimed to synthesize and quantify the associations of awareness of age-related change (AARC) with emotional well-being, physical well-being, and cognitive functioning. RESEARCH DESIGN AND METHODS: We conducted a systematic review with a correlational random effects meta-analysis. We included quantitative studies, published from January 1, 2009 to October 3, 2018, exploring associations between AARC and one or more of the following outcomes: emotional well-being, physical well-being, and cognitive functioning. We assessed heterogeneity (I2) and publication bias. RESULTS: We included 12 studies in the review, 9 exploring the association between AARC and emotional well-being and 11 exploring the association between AARC and physical well-being. No study explored the association between AARC and cognitive functioning. Six articles were included in the meta-analysis. We found a moderate association between a higher level of AARC gains and better emotional well-being (r = .33; 95% CI 0.18, 0.47; p <.001; I2 = 76.01) and between a higher level of AARC losses and poorer emotional (r = -.31; 95% CI -0.38, -0.24; p < .001; I2 = 0.00) and physical well-being (r = -.38; 95% CI -0.51, -0.24; p < .001; I2 = 83.48). We found a negligible association between AARC gains and physical well-being (r = .08; 95% CI 0.02, 0.14; p < .122; I2 = 0.00). Studies were of medium to high methodological quality. DISCUSSION AND IMPLICATIONS: There is some indication that AARC gains and losses can play a role in emotional well-being and that AARC losses are associated with physical well-being. However, the number of included studies is limited and there was some indication of heterogeneity. PROSPERO REGISTRATION: CRD42018111472.University of Exeter College of Life and Environmental Sciences (School of Psychology)University of Exeter College of Medicine and Healt

The associations between the response efficacy and objective and subjective change in physical activity and diet in the Information and Risk Modification trial

Objectives: Many health promotion campaigns and interventions focussing on improving health-related behaviours have been based on targeting response efficacy. This is based on the assumption that response efficacy is an important modifiable determinant of behaviour change. This study aimed to quantify the association between response efficacy and objective and subjective measures of physical activity and diet. Study design: Prospective cohort analysis of data from a randomised controlled trial. Methods: A total of 953 participants were assessed for response efficacy at baseline and 12 weeks following randomisation to interventions to increase physical activity and improve diet. Subjective measures were collected via a self-report questionnaire that included two questions used to derive the Cambridge Index of physical activity and questions about daily or weekly fruit and vegetable, whole grain, meat and fish intake, based on the dietary guidelines to lower cardiovascular risk. Objective measures were quantified using accelerometers and plasma carotenoids. Results: The mean change in response efficacy for physical activity was +0.5 (standard deviation SD 2.0) and for diet was +0.5 (SD 2.1).There were no clinically or statistically significant associations between baseline or change in response efficacy and objective and subjective measures of physical activity or objective measures of diet. There was a small statistically significant association between baseline response efficacy and change in self-reported wholegrain consumption, but this is unlikely to be clinically significant. Conclusions: Response efficacy is not a fundamental determinant of diet and physical activity and should not be the main focus of interventions targeting these behaviours. © 2018 The Author(s

Risk accuracy of type 2 diabetes in middle aged adults: Associations with sociodemographic, clinical, psychological and behavioural factors

Objective To identify the proportion of individuals with an accurate perception of their risk of type 2 diabetes (T2D) prior to, immediately after and eight weeks after receiving a personalised risk estimate. Additionally, we aimed to explore what factors are associated with underestimation and overestimation immediately post-intervention. Methods Cohort study based on the data collected in the Diabetes Risk Communication Trial. We included 379 participants (mean age 48.9 (SD 7.4) years; 55.1 women) who received a genotypic or phenotypic risk estimate for T2D. Results While only 1.3 of participants perceived their risk accurately at baseline, this increased to 24.7 immediately after receiving a risk estimate and then dropped to 7.3 at eight weeks. Those who overestimated their risk at baseline continued to overestimate it, whereas those who underestimated their risk at baseline improved their risk accuracy. We did not identify any other characteristics associated with underestimation or overestimation immediately after receiving a risk estimate. Conclusion Understanding a received risk estimate is challenging for most participants with many continuing to have inaccurate risk perception after receiving the estimate. Practice implications Individuals who overestimate or underestimate their T2D risk before receiving risk information might require different approaches for altering their risk perception. © 2017 The Author

Effect of interventions incorporating personalised cancer risk information on intentions and behaviour: A systematic review and meta-analysis of randomised controlled trials

Objective To provide a comprehensive review of the impact on intention to change health-related behaviours and health-related behaviours themselves, including screening uptake, of interventions incorporating information about cancer risk targeted at the general adult population. Design A systematic review and random-effects meta-analysis. Data sources An electronic search of MEDLINE, EMBASE, CINAHL and PsycINFO from 1 January 2000 to 1 July 2017. Inclusion criteria Randomised controlled trials of interventions including provision of a personal estimate of future cancer risk based on two or more non-genetic variables to adults recruited from the general population that include at least one behavioural outcome. Results We included 19 studies reporting 12 outcomes. There was significant heterogeneity in interventions and outcomes between studies. There is evidence that interventions incorporating personalised cancer risk information do not affect intention to attend or attendance at screening (relative risk 1.00 (0.97-1.03)). There is limited evidence that they increase smoking abstinence, sun protection, adult skin self-examination and breast examination, and decrease intention to tan. However, they do not increase smoking cessation, parental child skin examination or intention to protect skin. No studies assessed changes in diet, alcohol consumption or physical activity. Conclusions Interventions incorporating personalised cancer risk information do not affect uptake of screening, but there is limited evidence of effect on some health-related behaviours. Further research, ideally including objective measures of behaviour, is needed before cancer risk information is incorporated into routine practice for health promotion in the general population. Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted

Factors Associated With Engagement With a Web-Based Lifestyle Intervention Following Provision of Coronary Heart Disease Risk: Mixed Methods Study

Background: Web-based interventions provide the opportunity to combine the tailored approach of face-to-face interventions with the scalability and cost-effectiveness of public health interventions. This potential is often limited by low engagement. A number of studies have described the characteristics of individuals who engage more in Web-based interventions but few have explored the reasons for these variations. Objective: We aimed to explore individual-level factors associated with different degrees of engagement with a Web-based behavior change intervention following provision of coronary heart disease (CHD) risk information, and the barriers and facilitators to engagement. Methods: This study involved the secondary analysis of data from the Information and Risk Modification Trial, a randomized controlled trial of a Web-based lifestyle intervention alone, or alongside information on estimated CHD risk. The intervention consisted of three interactive sessions, each lasting up to 60 minutes, delivered at monthly intervals. Participants were characterized as high engagers if they completed all three sessions. Thematic analysis of qualitative data from interviews with 37 participants was combined with quantitative data on usage of the Web-based intervention using a mixed-methods matrix, and data on the views of the intervention itself were analyzed across all participants. Results: Thirteen participants were characterized as low engagers and 24 as high engagers. There was no difference in age (P=.75), gender (P=.95), or level of risk (P=.65) between the groups. Low engagement was more often associated with: (1) reporting a negative emotional reaction in response to the risk score (P=.029), (2) perceiving that the intervention did not provide any new lifestyle information (P=.011), and (3) being less likely to have reported feeling an obligation to complete the intervention as part of the study (P=.019). The mixed-methods matrix suggested that there was also an association between low engagement and less success with previous behavior change attempts, but the statistical evidence for this association was weak (P=.16). No associations were seen between engagement and barriers or facilitators to health behavior change, or comments about the design of the intervention itself. The most commonly cited barriers related to issues with access to the intervention itself: either difficulties remembering the link to the site or passwords, a perceived lack of flexibility within the website, or lack of time. Facilitators included the nonjudgmental presentation of lifestyle information, the use of simple language, and the personalized nature of the intervention. Conclusions: This study shows that the level of engagement with a Web-based intervention following provision of CHD risk information is not influenced by the level of risk but by the individual’s response to the risk information, their past experiences of behavior change, the extent to which they consider the lifestyle information helpful, and whether they felt obliged to complete the intervention as part of a research study. A number of facilitators and barriers to Web-based interventions were also identified, which should inform future interventions.The INFORM study was funded by European Commission Framework 7 EPIC-CVD Grant agreement (No. 279233). NHS Blood and Transplant funded the INTERVAL trial. Deoxyribonucleic acid extraction and genotyping in INTERVAL/INFORM was funded by the United Kingdom National Institute of Health Research. The coordinating team for INTERVAL/INFORM at the Cardiovascular Epidemiology Unit of the University of Cambridge was supported by core funding from: United Kingdom Medical Research Council (G0800270), British Heart Foundation (SP/09/002), British Heart Foundation Cambridge Cardiovascular Centre of Excellence, and United Kingdom National Institute for Health Research Cambridge Biomedical Research Centre. JUS was funded by a National Institute for Health Clinical Lectureship and BS was supported by the Medical Research Council (MC_UU_12015/4)

An assessment of relative habitat use as a metric for species' habitat association and degree of specialization

Corrigendum: Ecological Indicators, Volume 137, April 2022, Article number 108627, https://doi.org/10.1016/j.ecolind.2022.108627.In order to understand species' sensitivity to habitat change, we must correctly determine if a species is associated with a habitat or not, and if it is associated, its degree of specialization for that habitat. However, definitions of species' habitat association and specialization are often static, categorical classifications that coarsely define species as either habitat specialists or generalists and can fail to account for potential temporal or spatial differences in association or specialization. In contrast, quantitative metrics can provide a more nuanced assessment, defining species' habitat associations and specialization along a continuous scale and accommodate for temporal or spatial variation, but these approaches are less widely used. Here we explore relative habitat use (RHU) as a metric for quantifying species' association with and degree of specialization for different habitat types. RHU determines the extent of a species' association with a given habitat by comparing its abundance in that habitat relative to its mean abundance across all other habitats. Using monitoring data for breeding birds across Europe from 1998 to 2017; we calculate RHU scores for 246 species for five habitat types and compared them to the literature-based classifications of their association with and specialization for each of these habitats. We also explored the temporal variation in species' RHU scores for each habitat and assessed how this varied according to association and degree of specialization. In general, species' RHU and literature-derived classifications were well aligned, as RHU scores for a given habitat increased in line with reported association and specialization. In addition, temporal variation in RHU scores were influenced by association and degree of specialization, with lower scores for those associated with, and those more specialized to, a given habitat. As a continuous metric, RHU allows a detailed assessment of species' association with and degree of specialization for different habitats that can be tailored to specific temporal and/or spatial requirements. It has the potential to be a valuable tool for identifying indicator species and in supporting the design, implementation and monitoring of conservation management actions.Peer reviewe

Differences in health-related quality of life between Roma and non-Roma coronary heart disease patients: The role of hostility

Objectives: The aim of this study was to assess differences in health-related quality of life (HRQoL) between Roma and non-Roma coronary heart disease (CHD) patients, and whether differences in hostility contribute to this association. Methods: We examined 570 CHD patients (mean age 57.8, 28.1 female) scheduled for coronary angiography, 88 (15.4 ) of whom were Roma. Hostility was measured using the 27-item Cook-Medley Scale and HRQoL using the Short-Form Health Survey 36, from which the mental and physical component summary (MCS, PCS) were calculated. The relationship between ethnicity, hostility and HRQoL was examined using regression analyses. Results: Roma ethnicity was associated with poorer MCS (B = -3.44; 95 % CI = -6.76; -0.13 and poorer PCS (B = -4.16; 95 % CI = -7.55; -0.78) when controlled for age, gender and socioeconomic status. Adding hostility to the model weakened the strength of the association between Roma ethnicity and MCS (B = -1.87; 95 % CI = -5.08; 1.35) but not between Roma ethnicity and PCS (B = -4.07; 95 % CI = -7.50; -0.64). Conclusions: Roma ethnicity is associated with poorer MCS and PCS. Hostility may mediate the association between Roma ethnicity and MCS. The poorer HRQoL of Roma CHD patients requires attention in both care and research, with special attention on the role of hostility. © 2013 Swiss School of Public Health