Purpose After an acute coronary syndrome, referral to cardiac rehabilitation is essential for prevention of recurrent cardiac events. Improving physical activity (PA) and sedentary behaviour (SB) are important goals of cardiac rehabilitation, which, however, might be (much) more challenging in patients with obesity than in those with normal weight. We aimed to investigate the relation between body mass index (BMI) class and (changes in) PA and SB during and after cardiac rehabilitation in patients who were discharged after an acute coronary syndrome.

Methods This analysis is based on the OPTICARE trial. PA and SB were objectively measured with an Actigraph GT3X+ accelerometer at start, directly after completion of a multidisciplinary 12-week exercise-based cardiac rehabilitation program, and 9 months thereafter. Outcome measures were step count, and duration of time (% of wear time) spent in light PA, moderate-to-vigorous PA, and SB. Patients were classified as normal weight (BMI 18.5-24.99 kg/m2, n=82), overweight (BMI 25.0-29.99 kg/m2, n=182), or obese (BMI ≥ 30.0, n=95). Linear mixed-effects models were applied to study the relation between BMI class and (changes in) PA and SB.  

Results Patients (n=359) were 57.8 ± 8.9 years and 82.2% was male. At the start of cardiac rehabilitation, patients with overweight had similar PA and SB levels as those with normal weight. Patients with obesity made on average 952 steps/day less (5483 vs. 6435, p=0.010), spent 25 min/day less in light PA (3h 47min vs. 4h 12min, p=0.008), and 28 min/day more in SB (9h 40min vs. 9h 12min, p=0.011) than patients with normal weight. Improvements in PA and SB during cardiac rehabilitation were similar for all BMI classes (on average 507 steps/day more, 15min more in light PA, 5min more in moderate-to-vigorous PA, 20min less in SB). These improvements were maintained after completion of cardiac rehabilitation.  

Conclusions Patients with obesity started cardiac rehabilitation with a less favourable PA and SB profile than patients with normal weight. Because all BMI classes showed similar improvements during cardiac rehabilitation, this deficit was preserved. Reconsideration of the cardiac rehabilitation program for patients with obesity is warranted.

Purpose: The main aim of this study was to investigate the association between device-measured movement behaviours and risk of incident cardiovascular disease (CVD) in middle- to older-aged adults. A secondary aim was to develop an R package (“epicoda”) to facilitate epidemiological analyses using a Compositional Data Analysis (CoDA) approach to the exposure.

Methods: Between 2013 and 2015, participants in UK Biobank, a prospective cohort, were asked to wear a wristworn Axivity AX3 accelerometer for seven days. We applied a previously-developed machine-learning model to classify their movement behaviours as sleep, sedentary behaviour, light physical activity or moderate-to-vigorous physical activity. Using CoDA Cox regression, we investigated how reallocating time between movement behaviours was associated with CVD incidence. To support this analysis, we developed an R package to perform and present results of common epidemiological analyses, including linear, logistic and Cox regression analyses, using a CoDA approach to the exposure. This package, available at github.com:activityMonitoring/epicoda, also includes documentation (including worked examples) and automated testing.

Results/findings:
Among 87,499 UK Biobank participants, there were 3,492 incident CVD events over a median 5.4 years of follow-up. Reallocating time from any behaviour to moderate-to-vigorous physical activity (MVPA), or reallocating time from sedentary behaviour to any behaviour, was associated with lower CVD risk. For an average individual in our data, reallocating 20 minutes/day to MVPA from all other behaviours proportionally was associated with 9% (7%, 11%) lower risk, while reallocating 1 hour/day to sedentary behaviour was associated with 5% (3%, 7%) higher risk. This analysis was performed using “epicoda”, and the package has subsequently been used for other epidemiological analyses, including by users with no prior experience of CoDA.

Conclusions: Reallocating time from other behaviours to MVPA, or reallocating time from sedentary behaviour to other behaviours, was associated with lower risk of incident CVD. Interventions and guidelines should promote reallocating time to MVPA from other behaviours, and reallocating time from sedentary behaviour to light physical activity. By providing flexible functionality for common analyses, alongside detailed documentation, “epicoda” may further facilitate use of a CoDA approach in epidemiology. Feedback to improve and extend “epicoda” is welcomed.

Purpose: Examining a variety of methodologies for assessing diet quality will inform best practice use of diet quality indices for assessing health outcomes. This study examined the association between three diet quality indices (Dietary Guideline Index, DGI; Dietary Inflammatory Index, DII; Mediterranean-DASH Diet Intervention for Neurodegenerative Delay, MIND) and risk of all-cause and CVD mortality up to 19 years later.

Methods: Data on 9,083 adults (mean 50.4 years; 56% female) from the Australian Diabetes, Obesity and Lifestyle study were used. A food frequency questionnaire was used to calculate three diet quality indices at baseline: DGI, DII and MIND. Cox proportional hazard models were used to estimate hazard ratios (HR) and 95% Confidence Intervals of all-cause and CVD mortality according to each diet quality index. Models were adjusted for age, sex, education, smoking, medication, physical activity and energy intake.

Results: New deaths due to all-cause (n=1,423) and CVD (n=336) mortality were identified during mean follow-ups of 18.1 and 17.5 years, respectively. The adjusted HR associated with one-point higher DGI for all-cause mortality was 0.99 (95% CI: 0.99, 0.99) and for CVD mortality was 0.99 (0.98, 0.99). The adjusted HR associated with one-point higher DII for all-cause mortality was 1.05 (1.01, 1.09) and for CVD mortality was 1.09 (1.01, 1.18). The adjusted HR associated with one-point higher MIND for all-cause mortality was 0.94 (0.91, 0.97) and for CVD mortality was 0.91 (0.85, 0.98).

Conclusions: Higher DGI and MIND predicted lower risk of all-cause and CVD mortality up to 19 years later, while higher DII predicted higher risk. The present findings show the applicability of all three diet quality indices for assessing risk of all-cause and CVD mortality, while highlighting the benefit of following national dietary guidelines, a Mediterranean diet and a low inflammatory and neuroprotective diet.

Purpose: In recent years e-bikes have surged in popularity, with European sales predicted to increase from 3.7 million in 2019 to 17 million in 2030. The electrical assistance makes cycling more appealing to riders, while being of sufficient intensity to elicit positive health outcomes. Therefore, e-cycling may be acceptable for individuals with Type 2 Diabetes (T2D) who engage in less physical activity than their healthy counterparts. This study explored experiences of e-cycling among individuals with T2D, identifying key barriers and facilitators to engagement.

Methods: Semi-structured interviews were conducted with sixteen participants (Mean age=60, 50% female) from the intervention arm of a parallel-group two-arm randomized controlled pilot study (between October 2019 and March 2020). Participants received e-bike skills training and behavioural counselling prior to a 12-week e-bike loan. The interview guide was informed by the Theoretical Domains Framework. Data analysis followed the framework method and incorporated a deductive and inductive analytical approach.

Results: Participants were motivated to e-cycle as a means of improving their health, with limited consideration of potential environmental or financial impacts. A range of physical and mental health benefits were attributed to e-cycling, including improved fitness, mood and perceptible reductions in blood sugar levels. The electrical assistance enabled participants to ride faster, further and on hiller terrain than a conventional bicycle. These outcomes, and the ability to exercise outside, were associated with high e-cycling enjoyment, a key facilitator to engagement. For some participants the e-bike made cycling more accessible than conventional cycling. E-bike training provided participants with riding skills and enhanced road sense, thereby increasing e-cycling confidence. E-bikes were perceived as heavy, with some participants wanting smaller frames than usually recommended for their height to increase comfort. Barriers to e-cycling were primarily environmental including traffic, limited access to cycle paths, lack of safe parking and inadequate home storage. These barriers impacted riding for utilitarian purposes more than leisure riding.

Conclusions: E-cycling represents an appropriate and enjoyable form of physical activity for individuals with T2D.  E-cycling initiatives should focus on the potential health benefits of e-cycling with the provision of e-bike training to enhance cycling skills and confidence. 

Purpose: The maintenance of a healthy body weight can be challenging because of the omni-presence of tempting food cues. To deal with this temptation, one can compensate for moments of indulgence with a corresponding healthy behavior. This diet-related compensatory behavior can, for instance, mean that one engages in exercising after having consumed a calorie-rich meal the evening before. Because little is known about the influence of such behaviors on weight development, the aim of the present study was to investigate their effect on weight management over time in a non-clinical population.

Methods: Data from the first (2017) and third (2019) waves of the Swiss Food Panel 2.0, a longitudinal paper-and-pencil questionnaire, were analyzed. Participants (N₂₀₁₇ = 5238, N_2017-2019 = 2638) answered questions related to their diet-related compensatory behavior, eating behavior, and physical activity levels. Correlations and multiple linear regressions were performed to investigate cross-sectional and longitudinal relationships between diet-related compensatory behavior, diet quality, and physical activity as well as body mass index.

Results: On a cross-sectional level, diet-related compensatory behavior was positively correlated with diet quality for both sexes (men: r = .17, p < .001; women: r = .15, p < .001), with physical activity for women only (men: r = < .01, p = ns; women: r = .07, p < .01), and with body mass index for men only (men: r = .07, p < .001; women: r = .02, p = ns). Longitudinal results showed that more frequent diet-related compensatory behavior predicted significantly higher physical activity levels (b = .04, p < .01) and better diet quality (b = .05, p < .01) two years later, but no changes over time in body mass index (b = .01, p = ns).

Conclusions: When applied in healthy doses, diet-related compensatory behavior may contribute to the maintenance of a balanced and healthy body weight, but it does not seem to be a successful strategy for weight loss over time.

Purpose: Type 2 diabetes (T2D) prevalence is increasing in Kenya and prevention efforts, such as promoting healthier diets, are needed. Understanding local perceptions, experiences and factors influencing consumption of healthy diets is important to develop culturally coherent interventions to maximise engagement and potential effectiveness. The aim of this qualitative study was therefore to explore the barriers and enablers of consumption of healthy diets in two different communities in Nairobi, Kenya.

Methods: Participants were recruited from two contrasting communities in Nairobi: one low-income (n=15, 7 female) and one middle-income (n=14, 6 female). In-depth interviews were audio recorded, transcribed verbatim and translated to English (if conducted in Swahili). Thematic analysis using socioecological framework identified barriers and enablers of healthy diets across four levels of influence: individual, social environment (networks), physical environment (settings) and macro-level environment (societal norms and regulatory actions).

Findings: At individual level, barriers (-) and enablers (+) of healthy diets included: limited knowledge of healthy foods/drinks (-), health conditions such as stomach ulcers (+), eating for satiety or survival (-) in the low-income community, and preference of sweet taste (-). Social environment barriers and enablers were the influence of children on household diets (+/-), learning from the experiences of others (+), upbringing (+/-) and peer influence among middle-income participants (+/-). Physical environment barriers and enablers included: inaccessibility of healthy foods (-) mainly in the low-income community, accessibility of unhealthy foods (-) mainly in the middle-income community and eating out (-). Macro-level barriers were poor food safety regulations (which created safety concerns of vegetables) and societal norms (use of unhealthy foods as treats or rewards and association of some foods with socioeconomic status).

Conclusion: Interventions to promote healthy diets should target various areas of influence. Increase in knowledge of health foods at the individual level should be complemented by increasing accessibility of healthy foods in low-income communities and efforts to make healthy diets the default choice in more affluent communities. At the macro-level, food safety should be ensured in both communities to alleviate safety concerns in some healthy foods, such as vegetables.