Frequency of Diet and Physical Activity Goal Attainment and Barriers Encountered Among Adults With Type 2 Diabetes During a Telephone Coaching Intervention

Personalised lifestyle recommendations for type 2 diabetes: Design and simulation of a recommender system on UK Biobank Data

Mobile health applications, which employ wireless technology for healthcare, can aid behaviour change and subsequently improve health outcomes. Mobile health applications have been developed to increase physical activity, but are rarely grounded on behavioural theory and employ simple techniques for personalisation, which has been proven effective in promoting behaviour change. In this work, we propose a theoretically driven and personalised behavioural intervention delivered through an adaptive knowledge-based system. The behavioural system design is guided by the Behavioural Change Wheel and the Capability-Opportunity-Motivation behavioural model. The system exploits the ever-increasing availability of health data from wearable devices, point-of-care tests and consumer genetic tests to issue highly personalised physical activity and sedentary behaviour recommendations. To provide the personalised recommendations, the system firstly classifies the user into one of four diabetes clusters based on their cardiometabolic profile. Secondly, it recommends activity levels based on their genotype and past activity history, and finally, it presents the user with their current risk of developing cardiovascular disease. In addition, leptin, a hormone involved in metabolism, is included as a feedback biosignal to personalise the recommendations further. As a case study, we designed and demonstrated the system on people with type 2 diabetes, since it is a chronic condition often managed through lifestyle changes, such as physical activity increase and sedentary behaviour reduction. We trained and simulated the system using data from diabetic participants of the UK Biobank, a large-scale clinical database, and demonstrate that the system could help increase activity over time. These results warrant a real-life implementation of the system, which we aim to evaluate through human intervention.

Co-occurrence of hypertension and type 2 diabetes: prevalence and associated factors among Haramaya University employees in Eastern Ethiopia

Background

Both hypertension (HTN) and diabetes are public health concerns in low- and middle-income countries, particularly in sub-Saharan African countries. The co-occurrence of HTN and diabetes is associated with an increased risk of mortality, morbidity, and reduced productivity in the working force. In Ethiopia, there is limited evidence on the co-occurrence of HTN and type 2 diabetes (T2DM). Therefore, this study was conducted to assess the co-occurrence of HTN and T2DM and their associated factors among Haramaya University employees in Eastern Ethiopia.

Methods

A cross-sectional survey was conducted among 1,200 employees at Haramaya University using a simple random sampling technique from December 2018 to February 2019. Demographic and behavioral factors were collected on a semi-structured questionnaire, followed by measurement of anthropometry and blood pressure. Blood glucose and lipid profile measurements were performed by collecting 6 ml of venous blood samples after 8 h of overnight fasting. Data were entered into EpiData 3.1 version and analyzed using Stata 16 software. Bivariable and multivariable logistic regressions were applied to observe the association between independent variables with co-occurrence of HPN and T2DM using odds ratio, 95% confidence interval (CI), and p-values of ≤ 0.05 were considered statistically significant.

Results

The prevalence of HTN and T2DM was 27.3 and 7.4%, respectively. The co-occurrence of HTN and T2DM was 3.8%. The study found that being older (AOR = 3.97; 95 % CI: 1.80-8.74), khat chewing (AOR = 2.76; 95 % CI: 1.23-6.18), body mass index ≥ 25 kg/m² (AOR = 5.11; 95 % CI: 2.06-12.66), and sedentary behavior ≥8 h per day (AOR = 6.44; 95 % CI: 2.89-14.34) were statistically associated with co-occurrence of HTN and T2DM. On the other hand, consuming fruits and vegetables (AOR = 0.10; 95 % CI: 0.04-0.22) and a higher level of education (AOR = 0.39; 95% CI: 0.17-0.89) were negatively statistically associated with the co-occurrence of HTN and T2DM.

Conclusion

The co-occurrence of HTN and T2DM was prevalent among the study participants. This may create a substantial load on the healthcare system as an end result of increased demand for healthcare services. Therefore, rigorous efforts are needed to develop strategies for screening employees to tackle the alarming increase in HTN and T2DM in university employees.

Barriers to Weight Loss and Physical Activity, and Coach Approaches to Addressing Barriers, in a Real-World Adaptation of the DPP Lifestyle Intervention: A Process Analysis

PURPOSE

The purpose of this study is to identify barriers to weight loss and physical activity, as well as approaches used by coaches, in a real-world, community sample of adults with metabolic syndrome (at risk for type 2 diabetes) who participated in a Diabetes Prevention Program (DPP)-adapted weight loss intervention and compare findings to data from the screened and highly selected DPP sample.

METHODS

SHINE (Support, Health Information, Nutrition, and Exercise) was a telephonic DPP adaptation. Primary care staff delivered the DPP curriculum, and lifestyle coaches provided monthly direction to achieve weight loss. For this substudy, barriers to weight loss and physical activity described by participants, as well as approaches coaches used to address them, were gathered. Groupings of barriers (DPP defined) were analyzed in relation to demographic characteristics and compared to data from the DPP sample.

RESULTS

Top weight loss barriers were problems with self-monitoring, too little physical activity, internal thought/mood cues, vacation/holidays, and social cues. Percentages reporting a barrier were much higher in SHINE. Top physical activity barriers were problems with self-monitoring, access/weather, time management, aches/pains, and vacation/holidays. These did not correspond closely to DPP data. Coaches used problem solving, self-monitoring skills review, increased physical activity, and motivational strategies. SHINE coaches were more likely than DPP coaches to use alternative approaches.

CONCLUSIONS

Barriers to weight loss and physical activity in a community sample of persons at risk for diabetes occurred at much higher rates than in the highly screened DPP sample. Training coaches in a variety of patient-centered approaches may maximize their positive impact.