Recent global and regional reports consistently confirm the high and increasing prevalence of hypertension in sub-Saharan Africa (SSA), with poor detection, treatment, and control rates. This narrative review summarises the burden of hypertension in SSA and recent findings from community-based hypertension management strategies. We further outline prominent risk factors according to recent data and associated underlying mechanisms for hypertension development. An extensive review of literature showed that most countries have reported on the prevalence of hypertension during 2017–2023, despite limitations linked to the lack of nationally representative studies, heterogeneity of sampling and data collection methods. Task-shifting approaches that assign roles to model patients and community health workers reported improved linkage to healthcare services and adherence to medication, with inconsistent findings on blood pressure (BP)-lowering effects over time. The regularly reported risk factors include unhealthy diet, sedentary lifestyle, increased adiposity and underweight, ageing, level of education, and/or income as well as psychosocial factors. Newer data on the pathophysiological mechanisms leading to hypertension and potential areas of intervention are reported from children and adults and include, among others, salt-handling and volume overload, endothelial function, BP dipping patterns and the role of human immunodeficiency virus . To conclude, significant strides have been made in data reporting from SSA on the burden of hypertension in the region as well as biomarker research to improve understanding and identification of areas of intervention. However, gaps remain on linkage between knowledge generation, translation, and implementation research. Coordinated studies addressing both discovery science and public health are crucial to curb hypertension development and improve management in SSA.

There is a need for cost-effective weight management interventions that primary care can deliver to reduce the morbidity caused by obesity. Automated web-based interventions might provide a solution, but evidence suggests that they may be ineffective without additional human support. The main aim of this study was to carry out a feasibility trial of a web-based weight management intervention in primary care, comparing different levels of nurse support, to determine the optimal combination of web-based and personal support to be tested in a full trial. This was an individually randomised four arm parallel non-blinded trial, recruiting obese patients in primary care. Following online registration, patients were randomly allocated by the automated intervention to either usual care, the web-based intervention only, or the web-based intervention with either basic nurse support (3 sessions in 3 months) or regular nurse support (7 sessions in 6 months). The main outcome measure (intended as the primary outcome for the main trial) was weight loss in kg at 12 months. As this was a feasibility trial no statistical analyses were carried out, but we present means, confidence intervals and effect sizes for weight loss in each group, uptake and retention, and completion of intervention components and outcome measures. All randomised patients were included in the weight loss analyses (using Last Observation Carried Forward). At 12 months mean weight loss was: usual care group (n = 43) 2.44 kg; web-based only group (n = 45) 2.30 kg; basic nurse support group (n = 44) 4.31 kg; regular nurse support group (n = 47) 2.50 kg. Intervention effect sizes compared with usual care were: d = 0.01 web-based; d = 0.34 basic nurse support; d = 0.02 regular nurse support. Two practices deviated from protocol by providing considerable weight management support to their usual care patients. This study demonstrated the feasibility of delivering a web-based weight management intervention supported by practice nurses in primary care, and suggests that the combination of the web-based intervention with basic nurse support could provide an effective solution to weight management support in a primary care context. Current Controlled Trials ISRCTN31685626 .

Background: In June 2016, the Republic of South Africa introduced legislation for mandatory limits for the upper sodium content permitted in a wide range of processed foods. We assessed the sodium levels of packaged foods in South Africa during the one-year period leading up to the mandatory implementation date of the legislation. Methods: Data on the nutritional composition of packaged foods was obtained from nutrition information panels on food labels through both in-store surveys and crowdsourcing by users of the HealthyFood Switch mobile phone app between June 2015 and August 2016. Summary sodium levels were calculated for 15 food categories, including the 13 categories covered by the sodium legislation. The percentage of foods that met the government’s 2016 sodium limits was also calculated. Results: 11,065 processed food items were included in the analyses; 1851 of these were subject to the sodium legislation. Overall, 67% of targeted foods had a sodium level at or below the legislated limit. Categories with the lowest percentage of foods that met legislated limits were bread (27%), potato crisps (41%), salt and vinegar flavoured snacks (42%), and raw processed sausages (45%). About half (49%) of targeted foods not meeting the legislated limits were less than 25% above the maximum sodium level. Conclusion: Sodium levels in two-thirds of foods covered by the South African sodium legislation were at or below the permitted upper levels at the mandatory implementation date of the legislation and many more were close to the limit. The South African food industry has an excellent opportunity to rapidly meet the legislated requirements.

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. [J Med Internet Res 2008;10(4):e56]