Determining the frequency and level of task-sharing for hypertension management in LMICs: A systematic review and meta-analysis.

Background: Low- and middle-income countries (LMICs) bear a disproportionately higher burden of Cardiovascular Disease (CVD). Team-based care approach adds capacity to improve blood pressure (BP) control. This updated review aimed to test team-based care efficacy at different levels of hypertension team-based care complexity. Methods: We searched PubMed, Embase, Cochrane, and CINAHL for newer articles on task-sharing interventions to manage hypertension in LMICs. Levels of tasks complexity performed by healthcare workers added to the clinical team in hypertension control programs were categorized as administrative tasks (level 1), basic clinical tasks (level 2), and/or advanced clinical tasks (level 3). Meta-analysis using an inverse variance weighted random-effects model summarized trial-based evidence on the efficacy of team-based care on BP control, compared with usual care. Findings: Forty-three RCT articles were included in the meta-analysis: 31 studies from the previous systematic review, 12 articles from the updated search. The pooled mean effect for team-based care was a -4.6 mm Hg (95% CI: -5.8, -3.4, I2  = 80.2%) decrease in systolic BP compared with usual care. We found similar comparative reduction among different levels of team-based care complexity, i.e., administrative and basic clinical tasks (-4.7 mm Hg, 95% CI: -6.8, -2.2; I2  = 79.8%); and advanced clinical tasks (-4.5 mmHg, 95%CI: -6.1, -3.3; I2  = 81%). Systolic BP was reduced most by team-based care involving pharmacists (-7.3 mm Hg, 95% CI: -9.2, -5.4; I2  = 67.2%); followed by nurses (-5.1 mm Hg, 95% CI: -8.0, -2.2; I2  = 72.7%), dieticians (-4.7 mmHg, 95%CI: -7.1, -2.3; I2  = 0.0%), then community health workers (-3.3 mm Hg, 95% CI: -4.8, -1.8; I2  = 77.3%). Interpretation: Overall, team-based hypertension care interventions consistently contributed to lower systolic BP compared to usual care; the effect size varies by the clinical training of the healthcare team members. Funding: Resolve To Save Lives (RTSL) Vital Strategies, Danielle Cazabon, Andrew E. Moran, Yvonne Commodore-Mensah receive salary support from Resolve to Save Lives, an initiative of Vital Strategies. Resolve to Save Lives is jointly supported by grants from Bloomberg Philanthropies, the Bill & Melinda Gates Foundation, and Gates Philanthropy Partners, which is funded with support from the Chan Zuckerberg Foundation.

Core Strategies to Increase the Uptake and Use of Potassium-Enriched Low-Sodium Salt.

Excess sodium consumption and insufficient potassium intake contribute to high blood pressure and thus increase the risk of heart disease and stroke. In low-sodium salt, a portion of the sodium in salt (the amount varies, typically ranging from 10 to 50%) is replaced with minerals such as potassium chloride. Low-sodium salt may be an effective, scalable, and sustainable approach to reduce sodium and therefore reduce blood pressure and cardiovascular disease at the population level. Low-sodium salt programs have not been widely scaled up, although they have the potential to both reduce dietary sodium intake and increase dietary potassium intake. This article proposes a framework for a successful scale-up of low-sodium salt use in the home through four core strategies: availability, awareness and promotion, affordability, and advocacy. This framework identifies challenges and potential solutions within the core strategies to begin to understand the pathway to successful program implementation and evaluation of low-sodium salt use.

Priority Actions to Advance Population Sodium Reduction.

High sodium intake is estimated to cause approximately 3 million deaths per year worldwide. The estimated average sodium intake of 3.95 g/day far exceeds the recommended intake. Population sodium reduction should be a global priority, while simultaneously ensuring universal salt iodization. This article identifies high priority strategies that address major sources of sodium: added to packaged food, added to food consumed outside the home, and added in the home. To be included, strategies needed to be scalable and sustainable, have large benefit, and applicable to one of four measures of effectiveness: (1) Rigorously evaluated with demonstrated success in reducing sodium; (2) suggestive evidence from lower quality evaluations or modeling; (3) rigorous evaluations of similar interventions not specifically for sodium reduction; or (4) an innovative approach for sources of sodium that are not sufficiently addressed by an existing strategy. We identified seven priority interventions. Four target packaged food: front-of-pack labeling, packaged food reformulation targets, regulating food marketing to children, and taxes on high sodium foods. One targets food consumed outside the home: food procurement policies for public institutions. Two target sodium added at home: mass media campaigns and population uptake of low-sodium salt. In conclusion, governments have many tools to save lives by reducing population sodium intake.

Protocol for a cluster-randomized controlled trial of a technology-assisted health coaching intervention for weight management in primary care: The GEM (goals for eating and moving) study.

INTRODUCTION: Over one-third of American adults have obesity with increased risk of chronic disease. Primary care providers often do not counsel patients about weight management due to barriers such as lack of time and training. To address this problem, we developed a technology-assisted health coaching intervention called Goals for Eating and Moving (GEM) to facilitate obesity counseling within the patient-centered medical home (PCMH) model of primary care. The objective of this paper is to describe the rationale and design of a cluster-randomized controlled trial to test the GEM intervention when compared to Enhanced Usual Care (EUC). METHOD: We have randomized 19 PCMH teams from two NYC healthcare systems (VA New York Harbor Healthcare System and Montefiore Medical Group practices) to either the GEM intervention or EUC. Eligible participants are English and Spanish-speaking primary care patients (ages 18-69 years) with obesity or who are overweight with comorbidity (e.g., arthritis, sleep apnea, hypertension). The GEM intervention consists of a tablet-delivered goal setting tool, a health coaching visit and twelve telephone calls for patients, and provider counseling training. Patients in the EUC arm receive health education materials. The primary outcome is mean weight loss at 1 year. Secondary outcomes include changes in waist circumference, diet, and physical activity. We will also examine the impact of GEM on obesity-related provider counseling competency and attitudes. CONCLUSION: If GEM is found to be efficacious, it could provide a structured approach for improving weight management for diverse primary care patient populations with elevated cardiovascular disease risk.