Perceived and calculated diet quality improvements in a randomized mHealth weight loss trial.

The diet quality of US adults is poor and cross-sectional analyses suggest self-perception of healthful dietary intake may be overestimated. This analysis assessed the concordance between calculated and perceived diet quality and changes in diet quality among adults seeking weight loss and enrolled in a 12-month randomized behavioral trial. Healthy Eating Index-2015 diet quality (HEI) was calculated from self-administered 24-hour recalls. Perceived diet quality (PDQ) was measured on a 100-point scale. Higher scores indicate better diet quality. Concordance was assessed using the concordance correlation coefficient and Bland-Altman plots. The one hundred and five participants with complete dietary data were mostly female and white. There was good agreement between HEI and PDQ scores at 12 months for less than a third of participants. Most of the disagreement arose from PDQ scores being higher than HEI scores. Even fewer participants had good agreement between HEI changes and PDQ changes. Participants perceived greater improvement in diet quality than indicated by HEI score changes. Concordance was low at 12 months and for change in diet quality. Despite the diet quality of adults seeking weight loss being suboptimal and not improving, many perceived their diet quality and diet quality improvements as better than calculated. Future studies might explore the effect of misperceptions on weight loss outcomes.

Impact of lifestyle-based interventions on absolute cardiovascular disease risk: a systematic review and meta-analysis.

OBJECTIVE: The objective of the review was to synthesize the evidence of the effectiveness of lifestyle-based interventions for mitigating absolute cardiovascular disease (CVD) risk. INTRODUCTION: Evidence-based guidelines recommend employing an absolute CVD risk score to inform the selection and intensity of preventive interventions. However, studies employing this strategy have reported mixed results, hence the need for a systematic review of the current evidence. INCLUSION CRITERIA: Studies published in English that included a lifestyle-based intervention to mitigate CVD risk were considered. Studies were eligible if they enrolled individuals aged ≥18 years, with no history of CVD at baseline. The primary outcome was change in absolute CVD risk score post-intervention. METHODS: PubMed, Embase, and CINAHL searches were conducted from database inception to February 2022. The trial registers searched included Cochrane Central Register of Controlled Trials (CENTRAL) and ClinicalTrials.gov. Searches for unpublished studies/gray literature were conducted in ProQuest Dissertations and Theses Global, GreyLit Report, and OCLC First Search Proceedings. Two independent reviewers selected the studies and critically appraised them for methodological quality using JBI tools. Data extraction was performed for main outcome variables. Data were presented using separate pooled statistical meta-analysis for quasi-experimental and randomized clinical trials. Random effects models were employed in the analyses. Effect sizes (Cohen's d) were expressed as standardized mean difference at 95% CI. Heterogeneity was assessed via Cochran's Q statistic, and the inconsistency index ( I2 ) was used to describe variability in effect estimates due to heterogeneity rather than sampling error. RESULTS: Twenty-nine studies with a total sample of 5490 adults with no CVD at baseline were included. Fifteen were randomized controlled trials (RCTs; n=3605) and 14 were quasi-experimental studies (n=1885). The studies were conducted in Europe (n=18), the United States (n = 5), Asia (n=3), Mexico (n=1), Canada (n = 1), and Australia (n=1) and included the following lifestyle interventions: diet, physical activity, motivational interviewing, problem-solving, psychological counseling, cardiovascular risk assessment and feedback, health self-management education, and peer support. Six validated absolute CVD risk assessment tools were used to measure the study outcomes, including Framingham, SCORE, Heart Health Risk Assessment Score, Dundee, ASSIGN, and The UK Prospective Diabetes Study risk score. Overall, the methodological rigor of the RCTs and quasi-experimental studies was high. Of the 15 RCTs included in the meta-analysis, lifestyle intervention was favored over control in reducing absolute CVD risk score (Cohen's d = -0.39; P =0.032; Z= -2.14; I2 = 96). Similarly, in the 14 quasi-experimental studies, the absolute CVD risk score after lifestyle intervention was significantly lower compared to baseline (Cohen's d = -0.39; P <0.001; Z= -3.54; I2= 88). RCTs that combined diet and physical activity reported no significant impact on absolute CVD risk score, but those that used either intervention independently reported significant improvement in the absolute CVD risk score. CONCLUSIONS: There is evidence supporting the positive impact of lifestyle modification on absolute CVD risk score in adult populations without CVD. Our analysis further suggests that diet and physical activity had significant impact on absolute CVD risk, and a variety of validated screening tools can be used to monitor, evaluate, and communicate changes in absolute risk score after lifestyle modification. SUPPLEMENTAL DIGITAL CONTENT: A Spanish-language version of the abstract of this review is available [ http://links.lww.com/SRX/A29 ].

Feasibility and preliminary efficacy of a novel web-based physical activity intervention in adults with overweight/obesity: A pilot randomized controlled trial.

BACKGROUND: Only 14% of adults with obesity attain federal guidelines for physical activity (PA), but few interventions address obesity-specific barriers to PA. We designed the web-based Physical Activity for The Heart (PATH) intervention to address this gap. PURPOSE: Test the feasibility and preliminary efficacy of PATH for promoting PA and reducing cardiovascular disease (CVD) risk in adults with overweight/obesity. METHODS: In a 12-week pilot RCT, participants were randomized to PATH (n = 41) or wait-list control (n = 41) groups. Treatment group received access to PATH and met twice/month with a remote coach. The control group received a self-help PA guide and newsletters on general health. Moderate-to-vigorous PA (MVPA) was assessed via Actigraph-GT3X, steps via Fitbit Charge 2™, weight via smart scale, blood pressure (BP) via Omron BP device, and lipids/HbAIC via dry blood spot. Linear mixed modeling examined between- and within-group differences in PA and CVD risk. RESULTS: The sample (N = 82) was on average 55.9 ± 8.2 years old; mean BMI 35.5 ± 6.2 kg/m2; 57.3% white and 80.5% female. Recruitment lasted 6-months, and 12-week retention was 96.3%. Treatment group accessed PATH ≥twice/week (92.1%), spent ≥10 min/visit (89.5%) and thought the site was culturally appropriate (79%). At 12 wks, the PATH group had greater mean changes in weekly MVPA (+58.9 vs. +0.9 min, p = .024) and daily steps (+1246.4 vs. -64.2 steps, p = .002) compared to the control group. Also, the PATH group improved in weight, BMI, body fat, waist circumference, and BP (p < .05). CONCLUSION: The PATH intervention is feasible/acceptable and demonstrated preliminary efficacy for promoting PA among adults with overweight/obesity.

The Association between Neighborhood Walkability and Physical Activity in a Behavioral Weight Loss Trial Testing the Addition of Remotely Delivered Feedback Messages to Self-Monitoring.

Adding feedback messages (FB) to self-monitoring (SM) may reinforce behavior change. However, socio-environmental conditions (e.g., limited access to parks or low walkability) may limit one's ability to respond to FB focused on physical activity (PA). In this analysis, we hypothesized that high neighborhood walkability will positively modify the treatment effect of FB on PA, and residents of high walkability neighborhoods will achieve higher PA levels at 12 months than those in low walkability neighborhoods. The study is a secondary analysis of a 12-month behavioral weight-loss trial. Adults with overweight/obesity were randomized to SM + FB (n = 251) or SM alone (n = 251). SM + FB group received smartphone pop-up messages thrice/week tailored to their PA SM data. The assessment included neighborhood walkability via Walk Score (low [<50] vs. high [≥50]), moderate to vigorous PA (MVPA) and step count via Fitbit Charge 2™, and weight via smart scale. We report adjusted linear regression coefficients (b) with standard errors (SE). The analysis included participants who were primarily white, female, and with obesity. In adjusted models, neighborhood walkability did not moderate the effect of treatment assignment on log-transformed (ln) MVPA or steps count over 12 months. The SM + FB group had greater lnMVPA than the SM group, but lnMVPA and steps were similar between walkability groups. There were no significant interactions for group and time or group, time, and walkability. These findings suggest that adding FB to SM had a small but significant positive impact on PA over 12 months, but neighborhood walkability did not moderate the treatment effect of FB on PA.

Identifying Predictors of Adherence to the Physical Activity Goal: A Secondary Analysis of the SMARTER Weight Loss Trial.

INTRODUCTION/PURPOSE: Research is needed to inform tailoring supportive strategies for promoting physical activity (PA) in the context of behavioral treatment of obesity. We aimed to identify baseline participant characteristics and short-term intervention response predictors associated with adherence to the study-defined PA goal in a mobile health (mHealth) weight loss trial. METHODS: A secondary analysis was conducted of a 12-month weight loss trial (SMARTER) that randomized 502 adults with overweight or obesity to either self-monitoring of diet, PA, and weight with tailored feedback messages ( n = 251) or self-monitoring alone ( n = 251). The primary outcome was average adherence to the PA goal of ≥150 min·wk -1 of moderate- and vigorous-intensity aerobic activities (MVPA) from Fitbit Charge 2™ trackers over 52 wk. Twenty-five explanatory variables were considered. Machine learning methods and linear regression were used to identify predictors of adherence to the PA goal. RESULTS: The sample ( N = 502) was mostly female (80%), White (82%) with the average age of 45 ± 14.4 yr and body mass index of 33.7 ± 4.0 kg·m -2 . Machine learning methods identified PA goal adherence for the first week as the most important predictor of long-term PA goal adherence. In the parsimonious linear regression model, higher PA goal adherence for the first week, greater PA FB messages opened, older age, being male, higher education, being single and not having obstructive sleep apnea were associated with higher long-term PA goal adherence. CONCLUSIONS: To our knowledge, this is the first study using machine learning approaches to identify predictors of long-term PA goal adherence in a mHealth weight loss trial. Future studies focusing on facilitators or barriers to PA among young and middle-age adults and women with low PA goal adherence are warranted.

Neighborhood Walkability Is Associated with Physical Activity and Prediabetes in a Behavioral Weight Loss Study: a Secondary Analysis.

BACKGROUND: Socio-environmental factors may affect uptake and utility of behavioral interventions targeting weight loss and cardiometabolic health. To evaluate the relation of neighborhood walkability to physical activity (PA) and glucose control in a sample of adults with overweight/obesity participating in a weight loss study. METHODS: Secondary analysis of a 12-month behavioral weight loss intervention (2011-2015) using one-group pretest-posttest design. Neighborhood walkability was assessed via residential Walk Score (0-100) at study entry. Fasting plasma glucose (FPG) via phlebotomy and PA via waist-worn ActiGraph GT3X were assessed at baseline and end of study. Study variables included neighborhood walkability (car-dependent: Walk Score < 50 vs. walkable: Walk Score ≥ 50), prediabetes (FPG 100-125 mg/dL), and recommended PA (moderate to vigorous PA [MVPA] > 22 min/day). Generalized linear model with logit link results were reported as adjusted odds ratios (AOR) with 95% confidence intervals (CI). RESULTS: The sample (N = 114) was mostly female (88.6%), white (83.3%), college educated (73.7%), and on average 51.4 ± 1.0 years of age. At baseline, persons residing in car-dependent neighborhoods tended to have higher income than those in walkable neighborhoods. Neighborhood walkability interacted with household income at study entry to predict participants' ability to meet the MVPA goal at 12 months (AOR = 13.52, 95% CI: 1.86-119.20). Those from walkable neighborhoods had 67% lower odds of having prediabetes compared to those from car-dependent neighborhoods (AOR = 0.33, 95% CI: 0.10-0.87) at 12 months. CONCLUSION: Our findings corroborate previous research characterizing the relationship between neighborhood walkability, PA, and prediabetes status. Key drivers of this impact warrant further investigation in a study with a larger, more diverse sample.

Nightly Variation in Sleep Influences Self-efficacy for Adhering to a Healthy Lifestyle: A Prospective Study.

BACKGROUND: Self-efficacy, or the perceived capability to engage in a behavior, has been shown to play an important role in adhering to weight loss treatment. Given that adherence is extremely important for successful weight loss outcomes and that sleep and self-efficacy are modifiable factors in this relationship, we examined the association between sleep and self-efficacy for adhering to the daily plan. Investigators examined whether various dimensions of sleep were associated with self-efficacy for adhering to the daily recommended lifestyle plan among participants (N = 150) in a 12-month weight loss study. METHOD: This study was a secondary analysis of data from a 12-month prospective observational study that included a standard behavioral weight loss intervention. Daily assessments at the beginning of day (BOD) of self-efficacy and the previous night's sleep were collected in real-time using ecological momentary assessment. RESULTS: The analysis included 44,613 BOD assessments. On average, participants reported sleeping for 6.93 ± 1.28 h, reported 1.56 ± 3.54 awakenings, and gave low ratings for trouble sleeping (3.11 ± 2.58; 0: no trouble; 10: a lot of trouble) and mid-high ratings for sleep quality (6.45 ± 2.09; 0: poor; 10: excellent). Participants woke up feeling tired 41.7% of the time. Using linear mixed effects modeling, a better rating in each sleep dimension was associated with higher self-efficacy the following day (all p values < .001). CONCLUSION: Our findings supported the hypothesis that better sleep would be associated with higher levels of reported self-efficacy for adhering to the healthy lifestyle plan.

Effect of tailored, daily feedback with lifestyle self-monitoring on weight loss: The SMARTER randomized clinical trial.

OBJECTIVE: This study aimed to test the efficacy of self-monitoring and feedback (SM+FB) versus SM without FB (SM) in a behavioral weight-loss intervention at 6 months. METHODS: This was a randomized clinical trial. Eligibility criteria included the following: ≥18 years of age, BMI ≥ 27 and ≤43, smartphone user, and ability to engage in moderate physical activity. All participants received a 90-minute 1:1 counseling session, a Fitbit Charge 2, and a digital scale for SM. SM+FB participants were provided access to a customized smartphone application that provided three daily FB messages. The primary outcome was percentage of weight change from 0 to 6 months. RESULTS: The sample (N = 502) was 45 (SD 14.4) years old, BMI was 33.7 (SD 4.00) kg/m2 , 79.5% of participants were female (n = 399), and 84.3% were White (n = 423). At 6 months, there was 85.86% retention and a significant percentage of weight change in both groups (SM+FB: -3.16%, 95% CI: -3.85% to -2.47%, p < 0.0001; SM: -3.20%, 95% CI: -3.86% to -2.54%, p < 0.0001) but no significant between-group mean difference (-0.04%, 95% CI: -0.99% to 0.91%, p = 0.940). A ≥5% weight loss was achieved by 31.9% of the SM+FB group and 28.3% of the SM group. CONCLUSIONS: There was no significant between-group difference in weight loss at 6 months.

Obstructive Sleep Apnea Risk Is Associated With Severity of Metabolic Syndrome: A Secondary Analysis of the 2015-2018 National Health and Nutrition Examination Survey.

BACKGROUND: Metabolic syndrome (MetS) and obstructive sleep apnea (OSA) are associated with increased risk of cardiometabolic disease. The co-occurrence of OSA with MetS is common, but there are limited data on how OSA risk exacerbates the metabolic impairments present in MetS. The purpose of this analysis was to examine in a representative sample of participants in the National Health and Nutrition Examination Survey 2015-2018 cohorts (1) the association of modifiable cardiometabolic risk factors with OSA risk and MetS severity and (2) the influence of OSA risk and lifestyle behaviors on MetS severity. METHODS: Metabolic syndrome severity was assessed using MetS Z score, whereas the risk of OSA was measured via multivariable apnea prediction index. Data analyses were conducted using the sample weights provided by the National Health and Nutrition Examination Survey. RESULTS: The sample (N = 11 288) included adults (>20 years old) who were overweight (mean body mass index, 29.6 ± 0.2 kg/m 2 ), representative by race (36.9% non-White) and gender (51.9% female). Overall, 19.3% of the sample had elevated MetS severity (MetS Z score ≥ 1), and 38.4% were at a high risk of OSA (multivariable apnea prediction score of ≥0.50). High OSA risk was associated with having elevated MetS severity (odds ratio [OR], 4.94; 95% confidence interval [CI], 3.68-6.65). Obstructive sleep apnea risk predicted increased MetS severity (adjusted: B = 0.06, SE = 0.02, P = .013). Physical activity provided the highest protection from increased MetS severity (OR, 0.52; 95% CI, 0.39-0.70) and OSA risk (OR, 0.59; 95% CI, 0.53-0.66). CONCLUSION: Our findings suggest that increased OSA risk exacerbates MetS severity and that greater physical activity may mitigate the risk.

Sleep and Metabolic Syndrome.

Metabolic syndrome (MetS) refers to the clustering of risk factors for cardiovascular disease and diabetes, including central adiposity, hypertension, dyslipidemia, and hyperglycemia. During the past 20 years, there have been parallel and epidemic increases in MetS and impaired sleep. This article describes evidence on the association between MetS and short sleep duration, circadian misalignment, insomnia, and sleep apnea. Potential mechanisms where impaired sleep desynchronizes and worsens metabolic control and interventions to improve sleep and potentially improve MetS are presented.

The feasibility and acceptability of a web-based physical activity for the heart (PATH) intervention designed to reduce the risk of heart disease among inactive African Americans: Protocol for a pilot randomized controlled trial.

BACKGROUND: Many studies have used the internet to promote physical activity (PA) in several settings, including the home environment, but few have been tailored for African Americans (AAs). To address this research gap, we conducted focus groups with AAs to inform the development of a web-based intervention, Physical Activity for The Heart (PATH), that leverages openly accessible platforms, such as YouTube, to promote PA in any setting. PURPOSE: To describe the rationale and design of a pilot randomized clinical trial (RCT), that examines the feasibility and acceptability of the PATH intervention among 30 AA adults aged 40--70 years without history of cardiovascular disease. METHODS: A 12-week, single-site, wait-listed RCT with subjects randomized 1:1 to either: 1) treatment group - participants receive the PATH intervention, including the online portal and twice a month phone calls from a PA coach, or 2) attention control group - participants receive a self-help PA handout and twice a month general health newsletter. All participants self-monitor step count using actigraphy. The primary outcomes of this 12-week, pilot RCT are recruitment, retention, and adherence to self-monitoring (Actigraph wear time) and the intervention protocol (PATH utilization). The secondary outcomes include changes in PA (step count, moderate-to-vigorous PA, exercise self-efficacy), and cardiometabolic risk (HbA1C, HDL, LDL, total cholesterol, type 2 diabetes risk score, percent body fat, weight, and waist circumference) from baseline to 12 weeks. CONCLUSIONS: This study will provide PATH intervention feasibility and acceptability data among inactive AA adults and will inform a future, full-scale RCT testing efficacy.

Vicarious Experience in Multi-Ethnic Study of Atherosclerosis (MESA) Is Associated with Greater Odds of Attaining the Recommended Leisure-Time Physical Activity Levels.

BACKGROUND: Social cognitive theory posits that observing similar others succeed (i.e., vicarious experience) can improve self-efficacy. However, there are very limited data on the utility of vicarious experience in promoting physical activity (PA). This analysis examined the association between vicarious experience and leisure-time PA (LTPA) in the Multi-Ethnic Study of Atherosclerosis (MESA). METHODS: Cross-sectional analysis of MESA participants who completed exam 5. LTPA and neighborhood factors were self-reported. Neighborhood factors were converted into aesthetic, walking, and safety scores. Group comparative analyses evaluated differences in variables of interest. The relationship between vicarious experience and recommended LTPA (≥ 7.5 MET-h/week) was assessed via logistic regression. Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) are reported. RESULTS: Participants (N = 4579) were older (69.7 ± 9.4 years), 53% female, 41% Caucasian, 26% Black, 21% Hispanic, and 12% Chinese. Those who reported vicarious experience had 45% (95% CI 1.16-1.81) greater odds of attaining recommended LTPA. Unfavorable walking score was associated with lower odds of attaining recommended LTPA (OR = 0.89, 95% CI 0.79-1.00). The aesthetic and safety scales were not associated with LTPA (OR = 1.00 [95% CI 0.89-1.13] and OR = 0.91 [95% CI 0.82-1.10], respectively). CONCLUSIONS: Programs exposing community-dwelling adults to peers engaging in PA could provide an effective public health approach to increase community-level PA participation.

The association between sleep health and weight change during a 12-month behavioral weight loss intervention.

BACKGROUND: Prior research on the relationship between sleep and attempted weight loss failed to recognize the multidimensional nature of sleep. We examined the relationship between a composite measure of sleep health and change in weight and body composition among adults in a weight loss intervention. METHODS: Adults (N = 125) with overweight or obesity (50.3 ± 10.6 years, 91% female, 81% white) participated in a 12-month behavioral weight loss intervention, with assessments of sleep, weight, fat mass, and fat-free mass at baseline, 6 months, and 12 months. Six sleep dimensions (regularity, satisfaction, alertness, timing, efficiency, and duration) were categorized as "good" or "poor" using questionnaires and actigraphy. A composite score was calculated by summing the number of "good" dimensions. Obstructive sleep apnea (OSA) was assessed in a subsample (n = 117), using the apnea-hypopnea index (AHI) to determine OSA severity. Linear mixed modeling was used to examine the relationships between sleep health and outcomes of percent weight, fat mass, or fat-free mass change during the subsequent 6-month interval, adjusting for age, sex, bed partner, and race; an additional model adjusted for AHI. RESULTS: Mean baseline and 6-month sleep health was 4.5 ± 1.1 and 4.5 ± 1.2, respectively. Mean weight, fat mass, and fat-free mass changes from 0 to 6 months were -9.3 ± 6.1%, -16.9 ± 13.5%, and -3.4 ± 3.4%, respectively, and 0.4 ± 4.8%, -0.3 ± 10.3%, and 0.7 ± 4.1% from 6 to 12 months. Better sleep health was associated with greater subsequent weight loss (P = 0.016) and fat loss (P = 0.006), but not fat-free mass loss (P = 0.232). Following AHI adjustment, the association between sleep health and weight loss was attenuated (P = 0.102) but remained significant with fat loss (P = 0.040). Regularity, satisfaction, timing, and efficiency were each associated with weight and/or fat loss (P ≤ 0.041). CONCLUSIONS: Better sleep health was associated with greater weight and fat loss, with associations attenuated after accounting for OSA severity. Future studies should explore whether improving sleep health, OSA, or the combination improves weight loss.

Impact of lifestyle modification on absolute cardiovascular disease risk: a systematic review protocol.

OBJECTIVE: The objective of this review is to synthesize the available evidence on the effectiveness of lifestyle-based interventions for reducing absolute cardiovascular disease (CVD). INTRODUCTION: Cardiovascular disease prevention guidelines recommend tailoring the choice and intensity of preventive interventions based on absolute CVD risk score. Several studies employing lifestyle-based interventions to mitigate CVD risk have reported heterogeneous outcomes, necessitating a systematic review to provide an exhaustive summary of current evidence. INCLUSION CRITERIA: Eligible studies will include individuals at high-risk of CVD who are at least 18 years of age, with no history of CVD at baseline, regardless of sex, ethnicity and socio-economic status. Studies that compare lifestyle-based intervention to no intervention or usual care will be included. The outcome of interest is change in absolute CVD risk from baseline to post-intervention. Experimental and quasi-experimental study designs will be included. METHODS: Searches will be conducted in PubMed, EMBASE and CINAHL from the inception of each database. The search for gray literature will include ProQuest Dissertations and Theses Global, Grey Literature Report, Web of Science, BIOSIS Previews and the Proceedings database. Selected studies will be critically appraised by two independent reviewers at the study level for methodological quality. Extracted data will include details about the interventions, populations, study methods and outcomes of significance to the review question and objectives. Where possible, papers will be pooled in statistical meta-analysis. Effect sizes will be expressed as either odds ratios or standardized mean differences, and their 95% confidence intervals will be calculated for analysis. SYSTEMATIC REVIEW REGISTRATION NUMBER: PROSPERO CRD42017073543.

Recommendations for a Culturally Salient Web-based Physical Activity Program for African Americans.

BACKGROUND: Barriers to physical activity (PA) among African Americans (AAs) have been extensively studied, yet there is limited research on innovative PA interventions designed to address them. In recent years, many studies have used the internet to promote PA, but very few have included AAs. In this study, we sought the input of AA focus groups to inform the development of a web-based Physical Activity for The Heart (PATH) program for inactive AAs. METHODS: A qualitative design involving 4 focus groups stratified by sex and age was employed to explore AAs' needs and preferences for resources to be included in the PATH program. We employed an inductive approach to content analysis to analyze data using ATLAS.ti 7.5. RESULTS: Sixteen women and ten men (age 30-65 years) participated in the focus groups. Participants were obese (mean BMI 32.2 ± 5.4 kg/m2) with below average confidence rating (mean 46.4 ± 19.1%) on the Barriers Self-Efficacy Scale. Three main themes emerged from the data: 1) need to see similar others engaging in PA (workout videos featuring models with relatable body size, age, ethnicity), 2) flexible PA regimen (doable at any time/setting), and 3) age and sex differences in preferences for PA resources (religion, music, intensity). CONCLUSION: These data suggest that specific intervention components, i.e., PA models who match participants' profiles, flexibility and tailoring to age/gender groups, could improve uptake of web-based PA programs designed for inactive AAs. Therefore, a precision health approach needs to be employed when designing interventions to promote PA among inactive AAs.

Cost-effectiveness of the non-laboratory based Framingham algorithm in primary prevention of cardiovascular disease: A simulated analysis of a cohort of African American adults.

The non-lab Framingham algorithm, which substitute body mass index for lipids in the laboratory based (lab-based) Framingham algorithm, has been validated among African Americans (AAs). However, its cost-effectiveness and economic tradeoffs have not been evaluated. This study examines the incremental cost-effectiveness ratio (ICER) of two cardiovascular disease (CVD) prevention programs guided by the non-lab versus lab-based Framingham algorithm. We simulated the World Health Organization CVD prevention guidelines on a cohort of 2690 AA participants in the Atherosclerosis Risk in Communities (ARIC) cohort. Costs were estimated using Medicare fee schedules (diagnostic tests, drugs & visits), Bureau of Labor Statistics (RN wages), and estimates for managing incident CVD events. Outcomes were assumed to be true positive cases detected at a data driven treatment threshold. Both algorithms had the best balance of sensitivity/specificity at the moderate risk threshold (>10% risk). Over 12years, 82% and 77% of 401 incident CVD events were accurately predicted via the non-lab and lab-based Framingham algorithms, respectively. There were 20 fewer false negative cases in the non-lab approach translating into over $900,000 in savings over 12years. The ICER was -$57,153 for every extra CVD event prevented when using the non-lab algorithm. The approach guided by the non-lab Framingham strategy dominated the lab-based approach with respect to both costs and predictive ability. Consequently, the non-lab Framingham algorithm could potentially provide a highly effective screening tool at lower cost to address the high burden of CVD especially among AA and in resource-constrained settings where lab tests are unavailable.

Validation of the nonlaboratory-based Framingham cardiovascular disease risk assessment algorithm in the Atherosclerosis Risk in Communities dataset.

BACKGROUND: Nonlaboratory-based (non-LB) algorithms have been developed to facilitate absolute cardiovascular risk assessment in resource-constrained settings. The non-LB Framingham algorithm, which substitute BMI for lipids in laboratory-based Framingham, exhibits best performance among non-LB algorithms. However, its external validity has not been evaluated. AIM: To examine the validity of non-LB Framingham algorithm in Atherosclerosis Risk in Communities dataset, and contrast performance with the laboratory-based Framingham algorithm. METHODS: We developed Cox regression models including non-LB and laboratory-based Framingham covariates in Atherosclerosis Risk in Communities dataset. Discrimination was assessed via C-statistic, calibration via goodness-of-fit, and marginal discrimination value of BMI vis-à-vis lipids vis-à-vis waist-hip ratio via net reclassification improvement (NRI). Both models were compared via area under receiver operating characteristic. RESULTS: Among 11 601 participants (mean age 54 years, 55% women, 23% black), non-LB vs. laboratory-based Framingham performed as follows: C-statistic 0.75 vs. 0.76 among women and 0.67 vs. 0.68 among men; goodness-of-fit 14.2 vs. 10.5 among women and 25.8 vs. 21.8 among men. Overall area under receiver operating characteristic was 0.706 vs. 0.710, respectively, with no racial differences in discrimination or calibration. BMI and total cholesterol had no impact on NRI. Incremental predictive value of HDL was comparable with waist-hip ratio (category-less NRI = 0.34 vs. 0.31; categorical NRI = 0.06 vs. 0.05, P < 0.01). CONCLUSION: These results demonstrate the validity and limitations of the non-LB Framingham algorithm in a biracial cohort. Substituting BMI with a central adiposity metric such as waist-hip ratio or waist circumference could make the algorithm better or at par with the laboratory-based Framingham algorithm.

Methodological Challenges in Estimating Trends and Burden of Cardiovascular Disease in Sub-Saharan Africa.

Background. Although 80% of the burden of cardiovascular disease (CVD) is in developing countries, the 2010 global burden of disease (GBD) estimates have been cited to support a premise that sub-Saharan Africa (SSA) is exempt from the CVD epidemic sweeping across developing countries. The widely publicized perspective influences research priorities and resource allocation at a time when secular trends indicate a rapid increase in prevalence of CVD in SSA by 2030. Purpose. To explore methodological challenges in estimating trends and burden of CVD in SSA via appraisal of the current CVD statistics and literature. Methods. This review was guided by the Critical review methodology described by Grant and Booth. The review traces the origins and evolution of GBD metrics and then explores the methodological limitations inherent in the current GBD statistics. Articles were included based on their conceptual contribution to the existing body of knowledge on the burden of CVD in SSA. Results/Conclusion. Cognizant of the methodological challenges discussed, we caution against extrapolation of the global burden of CVD statistics in a way that underrates the actual but uncertain impact of CVD in SSA. We conclude by making a case for optimal but cost-effective surveillance and prevention of CVD in SSA.

Evaluation of the performance of existing non-laboratory based cardiovascular risk assessment algorithms.

BACKGROUND: The high burden and rising incidence of cardiovascular disease (CVD) in resource constrained countries necessitates implementation of robust and pragmatic primary and secondary prevention strategies. Many current CVD management guidelines recommend absolute cardiovascular (CV) risk assessment as a clinically sound guide to preventive and treatment strategies. Development of non-laboratory based cardiovascular risk assessment algorithms enable absolute risk assessment in resource constrained countries.The objective of this review is to evaluate the performance of existing non-laboratory based CV risk assessment algorithms using the benchmarks for clinically useful CV risk assessment algorithms outlined by Cooney and colleagues. METHODS: A literature search to identify non-laboratory based risk prediction algorithms was performed in MEDLINE, CINAHL, Ovid Premier Nursing Journals Plus, and PubMed databases. The identified algorithms were evaluated using the benchmarks for clinically useful cardiovascular risk assessment algorithms outlined by Cooney and colleagues. RESULTS: Five non-laboratory based CV risk assessment algorithms were identified. The Gaziano and Framingham algorithms met the criteria for appropriateness of statistical methods used to derive the algorithms and endpoints. The Swedish Consultation, Framingham and Gaziano algorithms demonstrated good discrimination in derivation datasets. Only the Gaziano algorithm was externally validated where it had optimal discrimination. The Gaziano and WHO algorithms had chart formats which made them simple and user friendly for clinical application. CONCLUSION: Both the Gaziano and Framingham non-laboratory based algorithms met most of the criteria outlined by Cooney and colleagues. External validation of the algorithms in diverse samples is needed to ascertain their performance and applicability to different populations and to enhance clinicians' confidence in them.