In Sub-Saharan Africa, both HIV/AIDS and anemia have considerable public health problems. Anemia has an adverse effect on treatment outcome and it decreases the quality of life among adult HIV patients. This study was aimed to assess the prevalence of anemia and its associated factors among adult HIV positive patients in Wolaita Sodo University Teaching Referral Hospital. Institution based cross-sectional study was conducted at Wolaita Sodo University Teaching Referral Hospital from 01 October to December 30, 2016. A randomly selected 411 adult people living with the human immunodeficiency virus were included in the study. A pre-tested questionnaire was used to collect data. Variables with P-value ≤0.25 in the bivariable logistic regression model were taken into multivariable logistic regression analysis along with 95% confidence interval and Odds Ratio was used to examine the association between anemia and independent variables. P˗value ≤ 0.05 was taken as statistically significant. Prevalence of anemia in this study was 36.5% with 95% CI (32%-41%). Factors associated with anemia among adult people living with HIV/AIDS were individuals who lived with HIV ≥9years (AOR = 2.6, 95% CI:-1.03–6.59),years lived with HIV 5–8 years (AOR = 2.59, 95% CI:-1.02–6.57),CD4 count <200cells/ul (AOR = 4.2, 95%CI:-2.03–8.67), CD4 count200-350cells/ul(AOR = 1.82,95%CI:-1.01–3.26),infection with intestinal parasites (AOR = 2.04, 95% CI:-1.06–3.95), Participants with BMI <18.5kg/m² (AOR = 2.96, 95%CI:-1.37–6.390),BMI 18.5-25kg/m²(AOR = 1.98, 95%CI:-1.11–3.56) and being HAART naïve (AOR = 2.23, 95% CI:- 1.16–4.28). Prevalence of anemia among this study participant was high. This may affect the treatment outcome, increases morbidity and mortality of the participants. So periodic screening of anemia, a routine checkup of nutritional status, CD4 count and examination for intestinal parasite are essential.

Fish by‐products, traditionally regarded as waste, are increasingly recognized as valuable sources of bioactive compounds, including peptides, omega‐3 fatty acids, collagen, and hydroxyapatite. These molecules exhibit significant functional properties with applications in food preservation, dietary supplementation, pharmaceuticals, and cosmeceuticals. This review explores advanced extraction technologies such as enzyme‐assisted hydrolysis, supercritical fluid extraction, and cold plasma processing, which enhance the yield and stability of bioactives while supporting zero‐waste and circular economy principles. Despite technological progress, key barriers remain, including inconsistent raw material quality, high processing costs, regulatory uncertainty, and limited industrial infrastructure. Peptides and protein hydrolysates derived from fish frames, skins, viscera, and scales have demonstrated antioxidant, antihypertensive, antimicrobial, antidiabetic activities, but translation into functional food and health products is constrained by scalability and regulatory challenges. Future work should focus on optimizing bioprocessing, validating health benefits through clinical trials, and implementing sustainable valorization frameworks. Addressing these challenges will unlock the full potential of fish by‐products in advancing food security and human health.

Background: Non-adherence to antihypertensive medications (AHMs) is a widespread problem. Cardiovascular morbidity and mortality reduction is possible via better adherence rates among hypertensive patients. Objectives: This study aimed to assess the prevalence of non-adherence to AHMs and its predictors among hypertensive patients who attended Mirwais Regional Hospital in Kandahar, Afghanistan. Methods: A cross-sectional study using random sampling method was conducted among hypertensive patients, aged ≥18 years in Mirwais Regional Hospital at a 6-month follow-up between October and December 2022. To assess non-adherence to AHMs, we employed the Hill-Bone Medication Adherence scale. A value below or equal to 80% of the total score was used to signify non-adherence. A multivariable binary logistic regression model was used to identify predictors of non-adherence to AHMs. Results: We used data from 669 patients and found that 47.9% (95%CI: 44.1–51.8%) of them were non-adherent to AHMs. The majority (71.2%) of patients had poorly controlled blood pressure (BP). The likelihood of non-adherence to AHMs was significantly higher among patients from low monthly-income households [Adjusted odds ratio (AOR) 1.70 (95%CI: 1.13–2.55)], those with daily intake of multiple AHMs [AOR 2.02 (1.29–3.16)], presence of comorbid medical conditions [AOR 1.68 (1.05–2.67), lack of awareness of hypertension-related complications [AOR 2.40 (1.59–3.63)], and presence of depressive symptoms [AOR 1.65 (1.14–2.38)]. Conclusion: Non-adherence to AHMs was high. Non-adherence to AHMs is a potential risk factor for uncontrolled hypertension and subsequent cardiovascular complications. Policymakers and clinicians should implement evidence-based interventions to address factors undermining AHMs adherence in Afghanistan.

Background: Diabetes poses a significant public health challenge, predominantly affecting low-and middle-income countries (LMICs), including in Sub-Saharan Africa (SSA). The evolving landscape characterized by resource constraints, gaps in availability and functionality of healthcare system, and socio-demographic impediments has compounded these challenges. As an example, self-care interventions have played a crucial role in diabetes care. However, the effectiveness of these interventions in the SSA remains insufficiently explored. Therefore, this systematic review evaluated the effectiveness and implementation approach of diabetes self-care interventions in SSA. Method: A comprehensive search was conducted across electronic databases including PubMed, Scopus, and Google Scholar, to identify studies focusing on diabetes self-care interventions in SSA from 2013 to 2023. The included studies reported interventions targeting dietary adherence, physical activity, medication adherence, blood glucose monitoring, foot care, and educational or support programs. The quality of the studies was assessed using the JBI checklist. Effectiveness was assessed through outcomes including glycemic control, adherence rate, complication reduction, and improvement in patient outcomes. Result: Overall, 38.5% of interventions result showed positive changes in either primary or secondary outcomes. Studies that employed diabetes self-management education showed positive changes in approximately 28.6% of cases. However, SMS text messaging interventions did not demonstrate significant changes in the measured outcomes. Of the 13 studies reviewed, 12 used randomized controlled trial designs, whereas one study employed a quasi-experimental approach. The total of participants across intervention and control groups was 3172 adults with diabetes. The interventions employed various strategies including diabetes self-management education led by nurses and other professionals, SMS text messaging for treatment adherence, and other targeted approaches. The duration of these interventions varied from 2 to 12 months. Specific interventions, such as glucose machine provision with training, family support with culturally tailored educations, and periodontal treatment, exhibited notable improvement in adherences and reductions in HbA1c levels. Conclusion: The review underscores the significance of diabetes self-care interventions in SSA, showing varying effectiveness levels across different strategies. It emphasizes the importance of tailored approaches and highlight interventions that have shown promising outcomes, providing insights for future research, policy, and healthcare strategies in the region.

Food waste poses global challenges to sustainability, human health, and the environment. Meat production significantly contributes to the byproducts generated during slaughter and processing. These by-products, which are rich in proteins and lipids, can be valorized via enzymatic hydrolysis or green extraction to produce bioactive peptides. These peptide activities and beneficial properties include antioxidant, antihypertensive, antimicrobial, and anti-inflammatory activities, and thus, have potential as functional foods and nutraceuticals. Notably, bioactive peptides can modulate gut microbiota by promoting beneficial species (e.g., Lactobacillus and Bifidobacterium) while suppressing pathogenic microbes. This interaction improves the integrity of the gut barrier, immune responses, and metabolic health. Integrating meat byproduct valorization within a circular economic framework does not reduce environmental pollution but also creates opportunities for sustainable food innovation. Despite advances in peptide extraction and application, key challenges remain, including large-scale production, taste optimization, and regulatory compliance. Future research should optimize production techniques, assess long-term health impacts, and explore industrial scalability.

Artificial intelligence (AI) is promptly changing the nature of food production and processing to increase safety, efficiency, quality assurance, and sustainability throughout the farm‐to‐fork chain. This review discusses the recent developments in AI in the food manufacturing industry, such as machine learning (ML), deep learning (Dl), computer vision (CV), hyperspectral imaging (HSI), robotics, Internet‐of‐Things (IoT) integration, and natural language processing. These technologies allow detecting contamination and fraud in real‐time, near‐perfect predictive maintenance less 30% unplanned downtime, automated quality checks with up to 96%–100% accuracy, AI‐enabled predictive maintenance (PdM) has demonstrated its effectiveness by decreasing unplanned downtime in industrial case studies through a reduction rate that reaches 30% of total downtime, resource‐efficient smart factories, and creative AI‐driven formulation of products. New paradigms include digital twins, explainable AI, computational gastronomy, and cultured meat production, highlighting the transformative power of AI. Some of the solutions include standardized datasets, lightweight architectures, federated learning, and scalable deployment training programs. When used responsibly, AI can help create food systems that meet regulatory requirements while achieving sustainable development goals and circular economy standards, and all three Sustainable Development Goals, like Zero Hunger (SDG 2), Responsible Consumption and Production (SDG 12), and Climate Action (SDG 13).