The role of collaborative, multistakeholder partnerships in reshaping the health management of patients with noncommunicable diseases during and after the COVID-19 pandemic.

BACKGROUND: Policies to combat the COVID-19 pandemic have disrupted the screening, diagnosis, treatment, and monitoring of noncommunicable (NCD) patients while affecting NCD prevention and risk factor control. AIMS: To discuss how the first wave of the COVID-19 pandemic affected the health management of NCD patients, identify which aspects should be carried forward into future NCD management, and propose collaborative efforts among public-private institutions to effectively shape NCD care models. METHODS: The NCD Partnership, a collaboration between Upjohn and the European Innovation Partnership on Active and Healthy Ageing, held a virtual Advisory Board in July 2020 with multiple stakeholders; healthcare professionals (HCPs), policymakers, researchers, patient and informal carer advocacy groups, patient empowerment organizations, and industry experts. RESULTS: The Advisory Board identified barriers to NCD care during the COVID-19 pandemic in four areas: lack of NCD management guidelines; disruption to integrated care and shift from hospital-based NCD care to more community and primary level care; infodemics and a lack of reliable health information for patients and HCPs on how to manage NCDs; lack of availability, training, standardization, and regulation of digital health tools. CONCLUSIONS: Multistakeholder partnerships can promote swift changes to NCD prevention and patient care. Intra- and inter-communication between all stakeholders should be facilitated involving all players in the development of clinical guidelines and digital health tools, health and social care restructuring, and patient support in the short-, medium- and long-term future. A comprehensive response to NCDs should be delivered to improve patient outcomes by providing strategic, scientific, and economic support.

Vital Signs: Predicted Heart Age and Racial Disparities in Heart Age Among U.S. Adults at the State Level.

INTRODUCTION: Cardiovascular disease is a leading cause of morbidity and mortality in the United States. Heart age (the predicted age of a person's vascular system based on their cardiovascular risk factor profile) and its comparison with chronological age represent a new way to express risk for developing cardiovascular disease. This study estimates heart age and differences between heart age and chronological age (excess heart age) and examines racial, sociodemographic, and regional disparities in heart age among U.S. adults aged 30-74 years. METHODS: Weighted 2011 and 2013 Behavioral Risk Factor Surveillance System data were applied to the sex-specific non-laboratory-based Framingham risk score models, stratifying the results by age and race/ethnic group, educational and income level, and state. These results were then translated into age-standardized heart age values, mean excess heart age was calculated, and the findings were compared across groups. RESULTS: Overall, average predicted heart age for adult men and women was 7.8 and 5.4 years older than their chronological age, respectively. Statistically significant (p<0.05) racial/ethnic, sociodemographic, and regional differences in heart age were observed: heart age among non-Hispanic black men (58.7 years) and women (58.9 years) was greater than other racial/ethnic groups, including non-Hispanic white men (55.3 years) and women (52.5 years). Excess heart age was lowest for men and women in Utah (5.8 and 2.8 years, respectively) and highest in Mississippi (10.1 and 9.1 years, respectively). CONCLUSIONS AND IMPLICATIONS FOR PUBLIC HEALTH PRACTICE: The predicted heart age among U.S. adults aged 30-74 years was significantly higher than their chronological age. Use of predicted heart age might 1) simplify risk communication and motivate more persons to live heart-healthy lifestyles and better comply with recommended therapeutic interventions, and 2) motivate communities to implement programs and policies that support cardiovascular health.

Web-based self-assessment health tools: who are the users and what is the impact of missing input information?

BACKGROUND: Web-based health applications, such as self-assessment tools, can aid in the early detection and prevention of diseases. However, there are concerns as to whether such tools actually reach users with elevated disease risk (where prevention efforts are still viable), and whether inaccurate or missing information on risk factors may lead to incorrect evaluations. OBJECTIVE: This study aimed to evaluate (1) evaluate whether a Web-based cardiovascular disease (CVD) risk communication tool (Heart Age tool) was reaching users at risk of developing CVD, (2) the impact of awareness of total cholesterol (TC), HDL-cholesterol (HDL-C), and systolic blood pressure (SBP) values on the risk estimates, and (3) the key predictors of awareness and reporting of physiological risk factors. METHODS: Heart Age is a tool available via a free open access website. Data from 2,744,091 first-time users aged 21-80 years with no prior heart disease were collected from 13 countries in 2009-2011. Users self-reported demographic and CVD risk factor information. Based on these data, an individual's 10-year CVD risk was calculated according to Framingham CVD risk models and translated into a Heart Age. This is the age for which the individual's reported CVD risk would be considered "normal". Depending on the availability of known TC, HDL-C, and SBP values, different algorithms were applied. The impact of awareness of TC, HDL-C, and SBP values on Heart Age was determined using a subsample that had complete risk factor information. RESULTS: Heart Age users (N=2,744,091) were mostly in their 20s (22.76%) and 40s (23.99%), female (56.03%), had multiple (mean 2.9, SD 1.4) risk factors, and a Heart Age exceeding their chronological age (mean 4.00, SD 6.43 years). The proportion of users unaware of their TC, HDL-C, or SBP values was high (77.47%, 93.03%, and 46.55% respectively). Lacking awareness of physiological risk factor values led to overestimation of Heart Age by an average 2.1-4.5 years depending on the (combination of) unknown risk factors (P<.001). Overestimation was greater in women than in men, increased with age, and decreased with increasing CVD risk. Awareness of physiological risk factor values was higher among diabetics (OR 1.47, 95% CI 1.46-1.50 and OR 1.74, 95% CI 1.71-1.77), those with family history of CVD (OR 1.22, 95% CI 1.22-1.23 and OR 1.43, 95% CI 1.42-1.44), and increased with age (OR 1.05, 95% CI 1.05-1.05 and OR 1.07, 95% CI 1.07-1.07). It was lower in smokers (OR 0.52, 95% CI 0.52-0.53 and OR 0.71, 95% CI 0.71-0.72) and decreased with increasing Heart Age (OR 0.92, 95% CI 0.92-0.92 and OR 0.97, 95% CI 0.96-0.97) (all P<.001). CONCLUSIONS: The Heart Age tool reached users with low-moderate CVD risk, but with multiple elevated CVD risk factors, and a heart age higher than their real age. This highlights that Web-based self-assessment health tools can be a useful means to interact with people who are at risk of developing disease, but where interventions are still viable. Missing information in the self-assessment health tools was shown to result in inaccurate self-health assessments. Subgroups at risk of not knowing their risk factors are identifiable and should be specifically targeted in health awareness programs.

The evaluation of goal-directed activities to promote well-being and health in heart failure: EUROIA scale.

BACKGROUND: The EvalUation of goal-diRected activities to prOmote well-beIng and heAlth (EUROIA) scale is a novel patient-reported measure that was administered to individuals with chronic heart failure (CHF). It assesses goal-directed activities that are self-reported as being personally meaningful and commonly utilized to optimize health-related quality of life (HRQL). Our aim was to evaluate psychometric properties of the EUROIA, and to determine if it accounted for novel variance in its association with clinical outcomes. METHODS: This study was a secondary analysis of the CHF-CePPORT trial, which enrolled 231 CHF patients: median age = 59.5 years, 23% women. Baseline assessments included: EUROIA, Kansas City Cardiomyopathy Questionnaire-Overall Summary (KCCQ-OS), Patient Health Questionnaire-9 for depression (PHQ-9), and the Generalized Anxiety Disorder-7 (GAD-7). 12-month outcomes included health status (composite index of incident hospitalization or emergency department, ED, visit) and mental health (PHQ-9 and GAD-7). RESULTS: Exploratory Principal Axis Factoring identified four EUROIA factors with satisfactory internal reliability: i.e., activities promoting eudaimonic well-being (McDondald's ω = 0.79), social affiliation (⍺=0.69), self-affirmation (⍺=0.73), and fulfillment of social roles/responsibilities (Spearman-Brown coefficient = 0.66). Multivariable logistic regression indicated that not only was the EUROIA inversely associated with incidence of 12-month hospitalization/ED visits independent of the KCCQ-OS (Odds Ratio, OR = 0.95, 95% Confidence Interval, CI, 0.91, 0.98), but it was also associated with 12-month PHQ-9 (OR = 0.91, 95% CI, 0.86, 0.97), and GAD-7 (OR = 0.94, 95% CI, 0.90, 0.99) whereas the KCCQ-OS was not. CONCLUSION: The EUROIA provides a preliminary taxonomy of goal-directed activities that promote HRQL among CHF patients independently from a current gold standard state-based measure. CLINICAL TRIAL REGISTRATION: NCT01864369; https://classic. CLINICALTRIALS: gov/ct2/show/NCT01864369 .

Share The Pressure.

This paper summarises 'Share The Pressure' (STP), a project that developed and piloted a scalable model for engaging patients on the benefits of risk factor control for healthy ageing; training healthcare professionals (HCPs) in cardiovascular disease (CVD) risk communication and to engage patients around the benefits of understanding risk factor control to enable healthy ageing (age- based approaches have been demonstrated to be motivating for patients). Thus, to improve shared decision-making processes between nurses, pharmacists, and patients. The study features the use of a CVD risk tool called Heart Age,3 which has been shown to effectively motivate risk factor reduction in individuals. The study team engaged virtually with patients and HCPs through established relationships within the community, third sector, charities, and social media. In addition, patients living with high blood pressure (hypertension) participated via online focus groups and surveys, which provided insight into patients' preferences for conveying CVD risk, quantification of intervention benefits, side effects and processes to facilitate shared decision-making. This insight gained from the focus group and survey data informed adaptations made to the Heart Age tool to provide 'years off' - or lowering of heart age - benefits for different aspects of blood pressure lowering, focusing on the independent and joint benefits of medication management and lifestyle. The study piloted a training programme for nurses and pharmacists to support them in communicating and framing risk and intervention benefits. The study trained 1,148 HCPs from 37 countries over 17 sessions. Post-training survey results of HCPs indicated an increase in self-rated knowledge and a strong likelihood of applying information learned to their clinical practice. In addition, the Heart Age users found the personalised report and Heart Age test results very motivating for patients with high blood pressure.

The Development and Evaluation of "Life Age"-a Primary Prevention and Population-Focused Risk Communication Tool: Feasibility Study With a Single-Arm Repeated Measures Design.

BACKGROUND: Communicating cardiovascular risk to the general population requires forms of communication that can enhance risk perception and stimulate lifestyle changes associated with reduced cardiovascular risk. OBJECTIVE: The aim of this study was to evaluate the motivational potential of a novel lifestyle risk assessment ("Life Age") based on factors predictive of both premature mortality and psychosocial well-being. METHODS: A feasibility study with a single-arm repeated measures design was conducted to evaluate the potential efficacy of Life Age on motivating lifestyle changes. Participants were recruited via social media, completed a web-based version of the Life Age questionnaire at baseline and at follow-up (8 weeks), and received 23 e-newsletters based on their Life Age results along with a mobile tracker. Participants' estimated Life Age scores were analyzed for evidence of lifestyle changes made. Quantitative feedback of participants was also assessed. RESULTS: In total, 18 of 27 participants completed the two Life Age tests. The median baseline Life Age was 1 year older than chronological age, which was reduced to -1.9 years at follow-up, representing an improvement of 2.9 years (P=.02). There were also accompanying improvements in Mediterranean diet score (P=.001), life satisfaction (P=.003), and sleep (P=.05). Quantitative feedback assessment indicated that the Life Age tool was easy to understand, helpful, and motivating. CONCLUSIONS: This study demonstrated the potential benefit of a novel Life Age tool in generating a broad set of lifestyle changes known to be associated with clinical risk factors, similar to "Heart Age." This was achieved without the recourse to expensive biomarker tests. However, the results from this study suggest that the motivated lifestyle changes improved both healthy lifestyle risks and psychosocial well-being, consistent with the approach of Life Age in merging the importance of a healthy lifestyle and psychosocial well-being. Further evaluation using a larger randomized controlled trial is required to fully evaluate the impact of the Life Age tool on lifestyle changes, cardiovascular disease prevention, and overall psychosocial well-being.

Web-based risk communication and planning in an obese population: exploratory study.

BACKGROUND: A healthy diet, low in saturated fat and high in fiber, is a popular medical recommendation in preventing cardiovascular disease (CVD). One approach to motivating healthier eating is to raise individuals' awareness of their CVD risk and then help them form specific plans to change. OBJECTIVES: The aim was to explore the combined impact of a Web-based CVD risk message and a fully automated planning tool on risk perceptions, intentions, and saturated fat intake changes over 4 weeks. METHODS: Of the 1187 men and women recruited online, 781 were randomly allocated to one of four conditions: a CVD risk message, the same CVD risk message paired with planning, planning on its own, and a control group. All outcome measures were assessed by online self-reports. Generalized linear modeling was used to analyze the data. RESULTS: Self-perceived consumption of low saturated fat foods (odds ratio 11.40, 95% CI 1.86-69.68) and intentions to change diet (odds ratio 21.20, 95% CI 2.6-172.4) increased more in participants allocated to the planning than the control group. No difference was observed between the four conditions with regard to percentage saturated fat intake changes. Contrary to our expectations, there was no difference in perceived and percentage saturated fat intake change between the CVD risk message plus planning group and the control group. Risk perceptions among those receiving the CVD risk message changed to be more in line with their age (change in slope(individual) = 0.075, P = .01; change in slope(comparative) = 0.100, P = .001), whereas there was no change among those who did not receive the CVD risk message. CONCLUSION: There was no evidence that combining a CVD risk message with a planning tool reduces saturated fat intake more than either alone. Further research is required to identify ways in which matching motivational and volitional strategies can lead to greater behavior changes.

Exploratory study of web-based planning and mobile text reminders in an overweight population.

BACKGROUND: Forming specific health plans can help translate good intentions into action. Mobile text reminders can further enhance the effects of planning on behavior. OBJECTIVE: Our aim was to explore the combined impact of a Web-based, fully automated planning tool and mobile text reminders on intention to change saturated fat intake, self-reported saturated fat intake, and portion size changes over 4 weeks. METHODS: Of 1013 men and women recruited online, 858 were randomly allocated to 1 of 3 conditions: a planning tool (PT), combined planning tool and text reminders (PTT), and a control group. All outcome measures were assessed by online self-reports. Analysis of covariance was used to analyze the data. RESULTS: Participants allocated to the PT (mean(saturatedfat) 3.6, mean(copingplanning) 3) and PTT (mean(saturatedfat) 3.5, mean(copingplanning) 3.1) reported a lower consumption of high-fat foods (F(2,571) = 4.74, P = .009) and higher levels of coping planning (F(2,571) = 7.22, P < .001) than the control group (mean(saturatedfat) 3.9, mean(copingplanning) 2.8). Participants in the PTT condition also reported smaller portion sizes of high-fat foods (mean 2.8; F(2,569) = 4.12, P = .0) than the control group (mean(portions) 3.1). The reduction in portion size was driven primarily by the male participants in the PTT (P = .003). We found no significant group differences in terms of percentage saturated fat intake, intentions, action planning, self-efficacy, or feedback on the intervention. CONCLUSIONS: These findings support the use of Web-based tools and mobile technologies to change dietary behavior. The combination of a fully automated Web-based planning tool with mobile text reminders led to lower self-reported consumption of high-fat foods and greater reductions in portion sizes than in a control condition. TRIAL REGISTRATION: International Standard Randomized Controlled Trial Number (ISRCTN): 61819220; http://www.controlled-trials.com/ISRCTN61819220 (Archived by WebCite at http://www.webcitation.org/63YiSy6R8).

Trajectories of entering the metabolic syndrome: the framingham heart study.

BACKGROUND: We evaluated the progression of the metabolic syndrome (MetS) and its components, the trajectories followed by individuals entering MetS, and the manner in which different trajectories predict cardiovascular disease and mortality. METHODS AND RESULTS: Using data from 3078 participants from the Framingham Offspring Study (a cohort study) who attended examinations 4 (1987), 5 (1991), and 6 (1995), we evaluated the progression of MetS and its components. MetS was defined according to the Adult Treatment Panel III criteria. Using logistic regression, we evaluated the predictive ability of the presence of each component of the MetS on the subsequent development of MetS. Additionally, we examined the probability of developing cardiovascular disease or mortality (until 2007) by having specific combinations of 3 that diagnose MetS. The prevalence of MetS almost doubled in 10 years of follow-up. Hyperglycemia and central obesity experienced the highest increase. High blood pressure was most frequently present when a diagnosis of MetS occurred (77.3%), and the presence of central obesity conferred the highest risk of developing MetS (odds ratio, 4.75; 95% confidence interval, 3.78 to 5.98). Participants who entered the MetS having a combination of central obesity, high blood pressure, and hyperglycemia had a 2.36-fold (hazard ratio, 2.36; 95% confidence interval, 1.54 to 3.61) increase of incident cardiovascular events and a 3-fold (hazard ratio, 3.09, 95% confidence interval, 1.93 to 4.94) increased risk of mortality. CONCLUSIONS: Particular trajectories and combinations of factors on entering the MetS confer higher risks of incident cardiovascular disease and mortality in the general population and among those with MetS. Intense efforts are required to identify populations with these particular combinations and to provide them with adequate treatment at early stages of disease.

Evaluation of a cardiovascular disease risk assessment tool for the promotion of healthier lifestyles.

BACKGROUND: Although percentage risk formats are commonly used to convey cardiovascular disease (CVD) risk, people find it difficult to understand these representations. AIMS: To compare the impact of providing a CVD risk message in either a traditional format (% risk) or using an analogy of risk (Heart-Age) on participants' risk perceptions and intention to make lifestyle changes. METHODS: Four hundred and thirteen men and women were randomly allocated to one of two conditions; CVD risk as a percentage or as a Heart-Age score (a cardiovascular risk adjusted age). RESULTS: There was a graded relationship between perceived and actual CVD risk only in those participants receiving a Heart-Age message (P<0.05). Heart-Age was more emotionally impactful in younger individuals at higher actual CVD risk (P<0.01). Self-reported emotional reactions further mediated the relationship between risk perception and intention to make lifestyle changes. CONCLUSION: This study found that the Heart-Age message significantly differed from percentage CVD risk score in risk perceptions and was more emotionally impactful in those participants at higher actual CVD risk levels.

Risk prediction tools in cardiovascular disease prevention: A report from the ESC Prevention of CVD Programme led by the European Association of Preventive Cardiology (EAPC) in collaboration with the Acute Cardiovascular Care Association (ACCA) and the Association of Cardiovascular Nursing and Allied Professions (ACNAP).

Risk assessment and risk prediction have become essential in the prevention of cardiovascular disease. Even though risk prediction tools are recommended in the European guidelines, they are not adequately implemented in clinical practice. Risk prediction tools are meant to estimate prognosis in an unbiased and reliable way and to provide objective information on outcome probabilities. They support informed treatment decisions about the initiation or adjustment of preventive medication. Risk prediction tools facilitate risk communication to the patient and their family, and this may increase commitment and motivation to improve their health. Over the years many risk algorithms have been developed to predict 10-year cardiovascular mortality or lifetime risk in different populations, such as in healthy individuals, patients with established cardiovascular disease and patients with diabetes mellitus. Each risk algorithm has its own limitations, so different algorithms should be used in different patient populations. Risk algorithms are made available for use in clinical practice by means of - usually interactive and online available - tools. To help the clinician to choose the right tool for the right patient, a summary of available tools is provided. When choosing a tool, physicians should consider medical history, geographical region, clinical guidelines and additional risk measures among other things. Currently, the U-prevent.com website is the only risk prediction tool providing prediction algorithms for all patient categories, and its implementation in clinical practice is suggested/advised by the European Association of Preventive Cardiology.

General cardiovascular risk profile for use in primary care: the Framingham Heart Study.

BACKGROUND: Separate multivariable risk algorithms are commonly used to assess risk of specific atherosclerotic cardiovascular disease (CVD) events, ie, coronary heart disease, cerebrovascular disease, peripheral vascular disease, and heart failure. The present report presents a single multivariable risk function that predicts risk of developing all CVD and of its constituents. METHODS AND RESULTS: We used Cox proportional-hazards regression to evaluate the risk of developing a first CVD event in 8491 Framingham study participants (mean age, 49 years; 4522 women) who attended a routine examination between 30 and 74 years of age and were free of CVD. Sex-specific multivariable risk functions ("general CVD" algorithms) were derived that incorporated age, total and high-density lipoprotein cholesterol, systolic blood pressure, treatment for hypertension, smoking, and diabetes status. We assessed the performance of the general CVD algorithms for predicting individual CVD events (coronary heart disease, stroke, peripheral artery disease, or heart failure). Over 12 years of follow-up, 1174 participants (456 women) developed a first CVD event. All traditional risk factors evaluated predicted CVD risk (multivariable-adjusted P<0.0001). The general CVD algorithm demonstrated good discrimination (C statistic, 0.763 [men] and 0.793 [women]) and calibration. Simple adjustments to the general CVD risk algorithms allowed estimation of the risks of each CVD component. Two simple risk scores are presented, 1 based on all traditional risk factors and the other based on non-laboratory-based predictors. CONCLUSIONS: A sex-specific multivariable risk factor algorithm can be conveniently used to assess general CVD risk and risk of individual CVD events (coronary, cerebrovascular, and peripheral arterial disease and heart failure). The estimated absolute CVD event rates can be used to quantify risk and to guide preventive care.

Risk prediction tools in cardiovascular disease prevention: A report from the ESC Prevention of CVD Programme led by the European Association of Preventive Cardiology (EAPC) in collaboration with the Acute Cardiovascular Care Association (ACCA) and the Association of Cardiovascular Nursing and Allied Professions (ACNAP).

Risk assessment and risk prediction have become essential in the prevention of cardiovascular disease. Even though risk prediction tools are recommended in the European guidelines, they are not adequately implemented in clinical practice. Risk prediction tools are meant to estimate prognosis in an unbiased and reliable way and to provide objective information on outcome probabilities. They support informed treatment decisions about the initiation or adjustment of preventive medication. Risk prediction tools facilitate risk communication to the patient and their family, and this may increase commitment and motivation to improve their health. Over the years many risk algorithms have been developed to predict 10-year cardiovascular mortality or lifetime risk in different populations, such as in healthy individuals, patients with established cardiovascular disease and patients with diabetes mellitus. Each risk algorithm has its own limitations, so different algorithms should be used in different patient populations. Risk algorithms are made available for use in clinical practice by means of - usually interactive and online available - tools. To help the clinician to choose the right tool for the right patient, a summary of available tools is provided. When choosing a tool, physicians should consider medical history, geographical region, clinical guidelines and additional risk measures among other things. Currently, the U-prevent.com website is the only risk prediction tool providing prediction algorithms for all patient categories, and its implementation in clinical practice is suggested/advised by the European Association of Preventive Cardiology.

Risk prediction tools in cardiovascular disease prevention: A report from the ESC Prevention of CVD Programme led by the European Association of Preventive Cardiology (EAPC) in collaboration with the Acute Cardiovascular Care Association (ACCA) and the Association of Cardiovascular Nursing and Allied Professions (ACNAP).

Risk assessment have become essential in the prevention of cardiovascular disease. Even though risk prediction tools are recommended in the European guidelines, they are not adequately implemented in clinical practice. Risk prediction tools are meant to estimate prognosis in an unbiased and reliable way and to provide objective information on outcome probabilities. They support informed treatment decisions about the initiation or adjustment of preventive medication. Risk prediction tools facilitate risk communication to the patient and their family, and this may increase commitment and motivation to improve their health. Over the years many risk algorithms have been developed to predict 10-year cardiovascular mortality or lifetime risk in different populations, such as in healthy individuals, patients with established cardiovascular disease and patients with diabetes mellitus. Each risk algorithm has its own limitations, so different algorithms should be used in different patient populations. Risk algorithms are made available for use in clinical practice by means of - usually interactive and online available - tools. To help the clinician to choose the right tool for the right patient, a summary of available tools is provided. When choosing a tool, physicians should consider medical history, geographical region, clinical guidelines and additional risk measures among other things. Currently, the U-prevent.com website is the only risk prediction tool providing prediction algorithms for all patient categories, and its implementation in clinical practice is suggested/advised by the European Association of Preventive Cardiology.

Using hypothetical data to assess the effect of numerical format and context on the perception of coronary heart disease risk.

PURPOSE: To test the hypothesis that responses to coronary heart disease (CHD) risk estimates are heightened by use of ratio formats, peer group risk information, and long time frames. DESIGN: Cross-sectional, experimental, between-factors design. SETTING: Three regions in England. SUBJECTS: A total of 740 men and women ages 30 to 70 years. MEASURES: Risk perception, "emotional" response, intention to change lifestyle. ANALYSIS: Logistic regression was used to investigate the impact of numerical format (ratio vs. percentage), peer group risk (personal vs. peer group), and time frame (10-year vs. 30-year) on risk perception. Analysis of variance was used to investigate the impact of these factors on emotional response and intention to change lifestyle questions. RESULTS: Higher perceived risk was observed when risk was presented as a ratio (p < .001) and when it was supplemented with peer group risk estimates (p = .006). Emotional responses to risk information were heightened when risk was presented as a ratio (p = .0004) and supplemented with peer group risk estimates (p = .002). Presentation with ratios also increased intention to make lifestyle changes (p = .047). CONCLUSION: Perception of CHD risk information is affected by the presentation format. Where absolute risks may appear low, use of ratios and supplementation of personal risk estimates with peer group risk may increase risk perception.

Sudden declines in intelligence in old age predict death and dropout from longitudinal studies.

It is well known that approaching death accelerates cognitive decline. The converse issue, that is, the question of whether rapid declines in cognitive ability are risk factors for imminent death, has not been investigated. Every 4 years between 1983 and 2003, we gave 1,414 healthy community residents who were aged between 49 and 93 years the Heim AH4-1 test of fluid intelligence. A modified Andersen-Gill model evaluated AH4-1 scores at entry to the study and changes in scores between successive quadrennial test sessions as risk factors for death and dropout. Deaths, dropouts, age, gender, occupational categories, and recruitment cohorts were also taken into account. Participants with lower AH4-1 scores on entry were significantly more likely to die or to drop out. At all ages and levels of baseline intelligence, the risks of deaths and dropouts further increased if test scores fell by 10%, and again increased if they fell by 20% during 4-year intervals between successive assessments.

Age and ability affect practice gains in longitudinal studies of cognitive change.

During a 20-year longitudinal study, 5,842 participants aged 49 to 93 years significantly improved over two to four successive experiences of the Heim AH4-1 intelligence test (first published in 1970), even with between-test intervals of 4 years and longer. After we considered significant attrition by death and dropout and the effects of gender, socioeconomic advantage, and recruitment cohort, we found that participants with high intelligence test scores showed greater improvement than did those with lower intelligence test scores. Practice gains also reduced with age, even after we took into consideration the individual differences in intelligence test scores. This emphasizes the methodological point that neglect of individual differences in improvement during longitudinal studies underestimates age-related changes in younger and more able participants and the theoretical point that, like all experiences during everyday life, participation in longitudinal studies alters the ability of aging humans to cope with cognitive demands to different extents according to their baseline abilities.

Rates and determinants of uptake and use of an internet physical activity and weight management program in office and manufacturing work sites in England: cohort study.

BACKGROUND: Internet-based physical activity (PA) and weight management programs have the potential to improve employees' health in large occupational health settings. To be successful, the program must engage a wide range of employees, especially those at risk of weight gain or ill health. OBJECTIVE: The aim of the study was to assess the use and nonuse (user attrition) of a Web-based and monitoring device-based PA and weight management program in a range of employees and to determine if engagement with the program was related to the employees' baseline characteristics or measured outcomes. METHODS: Longitudinal observational study of a cohort of employees having access to the MiLife Web-based automated behavior change system. Employees were recruited from manufacturing and office sites in the North West and the South of England. Baseline health data were collected, and participants were given devices to monitor their weight and PA via data upload to the website. Website use, PA, and weight data were collected throughout the 12-week program. RESULTS: Overall, 12% of employees at the four sites (265/2302) agreed to participate in the program, with 130 men (49%) and 135 women (51%), and of these, 233 went on to start the program. During the program, the dropout rate was 5% (11/233). Of the remaining 222 Web program users, 173 (78%) were using the program at the end of the 12 weeks, with 69% (153/222) continuing after this period. Engagement with the program varied by site but was not significantly different between the office and factory sites. During the first 2 weeks, participants used the website, on average, 6 times per week, suggesting an initial learning period after which the frequency of website log-in was typically 2 visits per week and 7 minutes per visit. Employees who uploaded weight data had a significant reduction in weight (-2.6 kg, SD 3.2, P< .001). The reduction in weight was largest for employees using the program's weight loss mode (-3.4 kg, SD 3.5). Mean PA level recorded throughout the program was 173 minutes (SE 12.8) of moderate/high intensity PA per week. Website interaction time was higher and attrition rates were lower (OR 1.38, P= .03) in those individuals with the greatest weight loss. CONCLUSIONS: This Web-based PA and weight management program showed high levels of engagement across a wide range of employees, including overweight or obese workers, shift workers, and those who do not work with computers. Weight loss was observed at both office and manufacturing sites. The use of monitoring devices to capture and send data to the automated Web-based coaching program may have influenced the high levels of engagement observed in this study. When combined with objective monitoring devices for PA and weight, both use of the website and outcomes can be tracked, allowing the online coaching program to become more personalized to the individual.

Lipoprotein particle profiles mark familial and sporadic human longevity.

BACKGROUND: Genetic and biochemical studies have indicated an important role for lipid metabolism in human longevity. Ashkenazi Jewish centenarians and their offspring have large low-density lipoprotein (LDL) and high-density lipoprotein (HDL) particles as compared with control individuals. This profile also coincided with a lower prevalence of disease. Here, we investigate whether this observation can be confirmed for familial longevity in an outbred European population and whether it can be extended to sporadic longevity in the general population. METHODS AND FINDINGS: NMR-measured lipoprotein profiles were analyzed in 165 families from the Leiden Longevity Study, consisting of 340 long-lived siblings (females >91 y, males >89 y), 511 of their offspring, and 243 partners of the offspring. Offspring had larger (21.3 versus 21.1 nm; p = 0.020) and fewer (1,470 versus 1,561 nmol/l; p = 0.011) LDL particles than their same-aged partners. This effect was even more prominent in the long-lived siblings (p < 10(-3)) and could be pinpointed to a reduction specifically in the concentration of small LDL particles. No differences were observed for HDL particle phenotypes. The mean LDL particle sizes in 259 90-y-old singletons from a population-based study were similar to those in the long-lived siblings and thus significantly larger than in partners of the offspring, suggesting that the relevance of this phenotype extends beyond familial longevity. A low concentration of small LDL particles was associated with better overall health among both long-lived siblings (p = 0.003) and 90-y-old singletons (p = 0.007). CONCLUSIONS: Our study indicates that LDL particle profiles mark both familial and sporadic human longevity already in middle age.

Estimated risks for developing obesity in the Framingham Heart Study.

BACKGROUND: The short- and long-term risks for developing overweight or obesity are unknown. OBJECTIVES: To estimate the short-term, long-term, and lifetime risks for developing overweight or obesity in adults in the community. DESIGN: Prospective cohort study, 1971 to 2001. SETTING: Community-based study, Framingham, Massachusetts. PARTICIPANTS: 4117 white participants (51.9% women) from the Framingham Heart Study. MEASUREMENTS: The short-term (4 years) and long-term (10 to 30 years) risks for ever becoming overweight or more (body mass index [BMI] > or = 25 kg/m2) or obese (BMI > or = 30 kg/m2) for men and women at 30, 40, and 50 years of age with a normal BMI (between 18.5 kg/m2 and 25.0 kg/m2). RESULTS: The observed 4-year rates of developing overweight varied from 14% to 19% in women and 26% to 30% in men. Four-year rates of developing obesity ranged from 5% to 7% in women and 7% to 9% in men. The long-term (30-year) risk estimates were similar for the 2 sexes generally; varied somewhat with age (in men, being lower for those 50 years of age); and, overall, exceeded 1 in 2 persons for overweight or more, 1 in 4 individuals for obesity, and 1 in 10 people for stage II obesity (BMI > or = 35 kg/m2) across different age groups. The 30-year estimates correspond to the residual lifetime risk for overweight or more or obesity for participants 50 years of age. LIMITATIONS: These findings may not be generalizable to other races or ethnicities. CONCLUSIONS: The long-term risks for overweight or more or obesity exceeded 50% and 25%, respectively, indicating a large public health burden. These estimates suggest that the future burden of obesity-associated diseases may be substantial.