Defining community-led monitoring and its role in programme-embedded learning: lessons from the Citizen Science Project in Malawi and South Africa.

INTRODUCTION: Programme Science (PS) and community-led monitoring (CLM) intersect in unexpected and promising ways. This commentary examines a CLM initiative in Malawi and South Africa to highlight the crucial role of CLM in bolstering the PS framework. By leveraging data sources often overlooked by conventional research and evaluation approaches, CLM emerges as a pivotal element in enhancing programme effectiveness. This paper delineates the fundamental principles of CLM, presents programme outcomes derived from CLM methodologies and contextualizes these findings within the broader framework of PS. DISCUSSION: The Citizen Science Project implements CLM continuously at 33 health facilities: 14 in Malawi (eight in Kasungu District and six in Dedza District), and 19 in South Africa (all in the West Rand District), representing a total catchment area of 989,848 people. Monitoring indicators are developed in an iterative process with community groups. The indicators are unique to each country, but both focus on the uptake of health services (quantitative) and barriers to access (qualitative). Monthly clinic records surveys capture 34 indicators in Malawi and 20 in South Africa and are supplemented by qualitative interviews with care recipients and healthcare workers. Qualitative interviews provide additional granularity and help confirm and explain the more macro trends in service coverage as described in quantitative data. The resulting data analysis reveals key themes that help stakeholders and decision-makers to solve problems collaboratively. Noteworthy outcomes include a substantial increase in multi-month dispensing of antiretroviral therapy (ART) during COVID-19 (from 6% to 31%) with a subsequent recovery surpassing of HIV service benchmarks in Malawi post-pandemic. CONCLUSIONS: While quantifying direct impact remains challenging due to the project's design, CLM proves to be a robust methodology that generates credible data and produces impactful outcomes. Its potential extends beyond the health sector, empowering community leadership and fostering interventions aligned with community needs. As CLM continues to evolve, its integration into PS promises to improve relevance, quality and impact across diverse disciplines.

The Transformative Impact of Community-Led Monitoring in the South African Health System: A Comprehensive Analysis.

Objectives: Community-led monitoring (CLM) is an emerging approach that empowers local communities to actively participate in data collection and decision-making processes within the health system. The research aimed to explore stakeholder perceptions of CLM data and establish a CLM Data Value Chain, covering data collection and its impact. Methods: Qualitative data were collected from stakeholders engaged in health programs in South Africa. Data analysis involved a collaborative workshop that integrated elements of affinity diagramming, thematic analysis, and the systematic coding process outlined in Giorgi's method. The workshop fostered joint identification, co-creation of knowledge, and collaborative analysis in developing the data value chain. Results: The findings showed that CLM data enabled community-level analysis, fostering program advocacy and local collaboration. It enhanced program redesign, operational efficiency, and rapid response capabilities. Context-specific solutions emerged through the CLM Data Value Chain, promoting sustainable and efficient program implementation. Conclusion: CLM is a powerful tool for improving program implementation, quality, and advocacy in South African healthcare. It strengthens accountability, trust, and transparency by involving local communities in data-driven decision-making. CLM addresses context-specific challenges and tailors interventions to local needs.

Physical behaviors and their association with type 2 diabetes mellitus risk markers in urban South African middle-aged adults: an isotemporal substitutionapproach.

INTRODUCTION: To examine the associations between physical behaviors and type 2 diabetes mellitus (T2DM) risk markers in middle-aged South African men and women. RESEARCH DESIGN AND METHODS: This cross-sectional study included middle-aged men (n=403; age: median (IQR), 53.0 (47.8-58.8) years) and women (n=324; 53.4 (49.1-58.1) years) from Soweto, South Africa. Total movement volume (average movement in milli-g) and time (minutes/day) spent in different physical behaviors, including awake sitting/lying, standing, light intensity physical activity (LPA) and moderate-to-vigorous intensity physical activity (MVPA), were determined by combining the signals from two triaxial accelerometers worn simultaneously on the hip and thigh. All participants completed an oral glucose tolerance test, from which indicators of diabetes risk were derived. Associations between physical behaviors and T2DM risk were adjusted for sociodemographic factors and body composition. RESULTS: Total movement volume was inversely associated with measures of fasting and 2-hour glucose and directly associated with insulin sensitivity, basal insulin clearance, and beta-cell function, but these associations were not independent of fat mass, except for basal insulin clearance in women. In men, replacing 30 min of sitting/lying, standing or LPA with the same amount of MVPA time was associated with 1.2-1.4 mmol/L lower fasting glucose and 12.3-13.4 mgl2/mUmin higher insulin sensitivity. In women, substituting sitting/lying with the same amount of standing time or LPA was associated with 0.5-0.8 mmol/L lower fasting glucose. Substituting 30 min sitting/lying with the same amount of standing time was also associated with 3.2 mgl2/mUmin higher insulin sensitivity, and substituting 30 min of sitting/lying, standing or LPA with the same amount of MVPA time was associated with 0.25-0.29 ng/mIU higher basal insulin clearance in women. CONCLUSION: MVPA is important in reducing T2DM risk in men and women, but LPA appears to be important in women only. Longitudinal and intervention studies warranted to provide more specific PA recommendations.

Physical Behaviors and Their Association With Adiposity in Men and Women From a Low-Resourced African Setting.

BACKGROUND: We first explored the associations between physical behaviors and total and regional adiposity. Second, we examined how reallocating time in different physical behaviors was associated with total body fat mass in men and women from a low-income South African setting. METHODS: This cross-sectional study included a sample of 692 participants (384 men and 308 women) aged 41-72 years. Physical behaviors were measured using integrated hip and thigh accelerometry to estimate total movement volume and time spent in sleeping, sitting/lying, standing, light physical activity, and moderate to vigorous physical activity (MVPA). Total body fat mass and regional adiposity were measured using dual-energy X-ray absorptiometry. RESULTS: The associations between total movement volume and measures of regional obesity were mediated by total body adiposity. In men, reallocating 30 minutes of sitting/lying to 30 minutes of MVPA was associated with 1.0% lower fat mass. In women, reallocation of 30 minutes of sitting/lying to MVPA and 30 minutes of standing to MVPA were associated with a 0.3% and 1.4% lower fat mass, respectively. CONCLUSIONS: Although the association between physical behaviors and fat mass differed between men and women, the overall public health message is similar; reallocating sedentary time to MVPA is associated with a reduction in fat mass in both men and women.

Sex Differences in the Associations of Nutrient Patterns with Total and Regional Adiposity: A Study of Middle-Aged Black South African Men and Women.

The study evaluated the association between nutrient patterns with body fat and regional adiposity in middle-aged black South African (SA) men and women and determined if this differed by sex. Body fat and regional adiposity (dual-energy x-ray absorptiometry), and dietary intake (7-day quantified food frequency questionnaire) were measured in black SA men (n = 414) and women (n = 346). Using principal component analysis, nutrient patterns were computed from 25 nutrients in the combined sample. Four nutrient patterns were extracted, explaining 67% of the variance in nutrient intake. Animal and fat, as well as the vitamin C, sugar, and potassium driven patterns, were positively associated with total adiposity. In contrast, the retinol and vitamin B12 pattern was associated with the centralisation of fat. Notably, the strength of the association between the animal-driven nutrient pattern and BMI was greater in men (1.14 kg/m2, 95% CI (0.63-1.66)) than in women (0.81 kg/m2, 95% CI (0.25-1.36)) (Pint = 0.017). In contrast, the plant-driven pattern was associated with higher abdominal subcutaneous adipose tissue (SAT) in women (44 cm2, 95% CI (22-67)) but not men (Pint = 1.54 × 10-4). These differences suggest that although men and women have similar nutrient patterns, their associations with the whole body and regional body fat are different.