Decoding the Weight-Hemoglobin Correlation in HIV-Positive Adults: Implications for Nutritional Interventions and Disease Management

Purpose
HIV-associated wasting and anemia are critical comorbidities that persist despite antiretroviral therapy (ART), creating a vicious cycle of declining health. This study aims to precisely quantify the relationship between body weight and hemoglobin (Hb) levels to guide integrated, targeted interventions that move beyond siloed treatment approaches.
Methods
We conducted a retrospective cohort analysis of 38 HIV-positive adults on ART (30 males, 8 females), identified during blood donation screening. Anthropometric and hematological data were extracted from electronic health records. The relationship between weight (kg) and Hb (g/dL) was analyzed using robust statistical methodologies in Python, including Spearman’s correlation and multivariate linear regression, controlling for sex, age, and ART duration. A machine learning framework (Random Forest) was implemented for predictive validation.
Results
Analysis revealed a powerful positive correlation between weight and Hb (ρ = 0.82, *p* < 0.001). Multivariable regression confirmed weight as a highly significant independent predictor, with every 10 kg increase associated with a +1.2 g/dL gain in Hb (β = 0.12, 95% CI: 0.08–0.16, *p* < 0.001). A profound sex-based disparity was identified, with female sex independently associated with a -1.45 g/dL Hb deficit (*p* = 0.001). The machine learning model validated weight as the paramount predictive feature (importance score = 0.89), forming the basis of a clinical prediction tool (AUC = 0.84).
Conclusion
Body weight is a robust, modifiable predictor of hematologic status in HIV patients, independent of ART. These findings mandate a paradigm shift toward integrating proactive nutritional support with standard ART. We propose the immediate adoption of weight-based risk stratification in clinical guidelines and the implementation of sex-specific interventions to disrupt the wasting-anemia cycle and improve long-term outcomes.

HIV anemia, nutritional status, body weight

1. Magura, J., Nhari, S. R., & Nzimakwe, T. I. (2025). Barriers to ART adherence in sub-Saharan Africa: a scoping review toward achieving UNAIDS 95-95-95 targets. Frontiers in Public Health, 13, 1609743. [Google Scholar] [Crossref]

2. Long, Y. (2024). Authoritarian Absorption: The Transnational Remaking of Epidemic Politics in China. Oxford University Press. [Google Scholar] [Crossref]

3. Reilly, J. B., Kim, J. G., Cooney, R., DeWaters, A. L., Holmboe, E. S., Mazotti, L., & Gonzalo, J. D. (2024). Breaking down silos between medical education and health systems: creating an integrated multilevel data model to advance the systems-based practice competency. Academic Medicine, 99(2), 146-152. [Google Scholar] [Crossref]

4. Saberi, M. A., Mcheick, H., & Adda, M. (2025). From data silos to health records without borders: a systematic survey on patient-centered data interoperability. Information, 16(2), 106. [Google Scholar] [Crossref]

5. Yeneakal, K. A., Teferi, G. H., Mihret, T. T., Mengistu, A. K., Tizie, S. B., & Tadele, M. M. (2025). Predicting antiretroviral therapy adherence status of adult HIV-positive patients using machine-learning Northwest, Ethiopia, 2025. BMC Medical Informatics and Decision Making, 25(1), 259. [Google Scholar] [Crossref]

6. Jain, A., Lim, C. P., & Jain, L. C. (Eds.). (2025). Digital Transformation in Healthcare Systems for Patient Care: Dedicated to Professor Dr. Gloria Phillips-Wren (Vol. 279). Springer Nature. [Google Scholar] [Crossref]

7. Bedimo, R., Hardy, D., Lee, D., Palella, F., & Wohl, D. (2024). Expert Consensus Statement on an Updated Definition of Unintended Weight Loss Among Persons With Human Immunodeficiency Virus in the Modern Treatment Era. Clinical Infectious Diseases, 79(Supplement_2), S63-S75. [Google Scholar] [Crossref]

8. Balaji, S., Chakraborty, R., & Aggarwal, S. (2024). Neurological complications caused by human immunodeficiency virus (HIV) and associated opportunistic co-infections: A review on their diagnosis and therapeutic insights. CNS & Neurological Disorders-Drug Targets-CNS & Neurological Disorders), 23(3), 284-305. [Google Scholar] [Crossref]

9. Katzschner, K., Wichelhaus, T., Wolf, T., Marx, B., Dahmer, I., Paulitsch, M., ... & Stephan, C. (2025). Delayed CD4 cell recovery in HIV-associated disseminated non-tuberculous mycobacterial disease: a case-control study. International Journal of Infectious Diseases, 108037. [Google Scholar] [Crossref]

10. Obeagu, E. I., Obeagu, G. U., Ukibe, N. R., & Oyebadejo, S. A. (2024). Anemia, iron, and HIV: decoding the interconnected pathways: A review. Medicine, 103(2), e36937. [Google Scholar] [Crossref]

11. Soni, R., Verma, D., Chopra, R., Singh, V., & Goswami, D. (2025). Demystifying Intricate Factors of Nutritional Anemia Beyond Iron Deficiency-A Narrative Review. Clinical Nutrition ESPEN. [Google Scholar] [Crossref]

12. Pinheiro, S. M. D. (2024). Impact of Diabetes on Response to Image-Guided Hydrodistension Treatment of Adhesive Capsulitis (Doctoral dissertation, Universidade do Porto (Portugal)). [Google Scholar] [Crossref]

13. Canny, S. P., Orozco, S. L., Thulin, N. K., & Hamerman, J. A. (2023). Immune mechanisms in inflammatory anemia. Annual review of immunology, 41(1), 405-429. [Google Scholar] [Crossref]

14. Housni, F. E., Saenz-Pardo-Reyes, E., Larios, M. D. J. L., Cañedo, C. L., Cervantes, V. G. A., & Lares-Michel, M. (2022). Association between nutritional status, deficiency of protein, iron and vitamins, caloric intake and food security in Mexi-can school children. Progr Nutr, 24(1), 2022013. [Google Scholar] [Crossref]

15. Kerebeh, G., Ayalew, Y., Kefale, D., Chanie, E. S., Misganaw, N. M., Feleke, D. G., ... & Endalamaw, A. (2022). Incidence of anemia and predictors among Human Immunodeficiency Virus-infected children on antiretroviral therapy at public health facilities of Bahir Dar City, Northwest Ethiopia: multicenter retrospective follow up study. BMC pediatrics, 22(1), 115. [Google Scholar] [Crossref]

16. Dessie, G., Li, J., Nghiem, S., & Doan, T. (2025). Prevalence and determinants of stunting-anemia and wasting-anemia comorbidities and micronutrient deficiencies in children under 5 in the least-developed countries: a systematic review and meta-analysis. Nutrition reviews, 83(2), e178-e194. [Google Scholar] [Crossref]

17. Nicholson, C. (2021). A synthesis of the work of CCAFS and partners on climate change and food and nutrition security. [Google Scholar] [Crossref]

18. Mwangi, M. N., Mzembe, G., Moya, E., & Verhoef, H. (2021). Iron deficiency anaemia in sub-Saharan Africa: a review of current evidence and primary care recommendations for high-risk groups. The Lancet Haematology, 8(10), e732-e743. [Google Scholar] [Crossref]

19. Gomes, F. L., Jeong, S. H., Shin, S. R., Leijten, J., & Jonkheijm, P. (2024). Engineering Synthetic Erythrocytes as Next‐Generation Blood Substitutes. Advanced functional materials, 34(28), 2315879. [Google Scholar] [Crossref]

20. Kamau, D. M., Kangethe, S., & Essuman, S. (2024). Prevalence and Underlying Factors of Anemia Among Adult HIV Patients Undergoing Highly Active Antiretroviral Therapy at Murang’a Level 5 Hospital, Kenya. Journal of Medical and Biomedical Laboratory Sciences Research, 4(1). [Google Scholar] [Crossref]

21. Fuseini, H., Gyan, B. A., Kyei, G. B., Heimburger, D. C., & Koethe, J. R. (2021). Undernutrition and HIV infection in sub-Saharan Africa: health outcomes and therapeutic interventions. Current HIV/AIDS Reports, 18(2), 87-97. [Google Scholar] [Crossref]

22. Munro, M. G., Mast, A. E., Powers, J. M., Kouides, P. A., O’Brien, S. H., Richards, T., ... & Levy, B. S. (2023). The relationship between heavy menstrual bleeding, iron deficiency, and iron deficiency anemia. American journal of obstetrics and gynecology, 229(1), 1-9. [Google Scholar] [Crossref]

23. Browne, A. (2021). Epidemiology of blood donor health in the context of increased frequency of donation: The INTERVAL trial (Doctoral dissertation). [Google Scholar] [Crossref]

24. Piekarska, A., Pawelec, K., Szmigielska-Kapłon, A., & Ussowicz, M. (2024). The state of the art in the treatment of severe aplastic anemia: immunotherapy and hematopoietic cell transplantation in children and adults. Frontiers in immunology, 15, 1378432. [Google Scholar] [Crossref]

25. Huynh, E. (2023). Physical Activity and Markers of Cardiovascular Health: Understanding the Influence of Menopause and Stroke (Doctoral dissertation). [Google Scholar] [Crossref]

26. Lionello, L., Counil, E., & Henry, E. (2021). Measuring health at a global level with a unified tool: A review of institutional and methodological milestones of the Global Burden of Disease project. [Google Scholar] [Crossref]

27. Buslón, N., Racionero-Plaza, S., & Cortés, A. (2022). Sex and gender inequality in precision medicine: socioeconomic determinants of health. In Sex and Gender Bias in Technology and Artificial Intelligence (pp. 35-54). Academic Press. [Google Scholar] [Crossref]

28. Yukthi, H. S., Vandana, W. M., & Khushi, E. C. (2024, May). Clinical Decision Support System for Anemia Identification and Severity Stratification. In 2024 International Conference on Electronics, Computing, Communication and Control Technology (ICECCC) (pp. 1-6). IEEE. [Google Scholar] [Crossref]

29. Deotale, T., & Saha, S. (2025, March). Review of Machine Learning Applications in HB Detection and Anaemia Screening Prognosis Under Clinical Conditions. In Future of Information and Communication Conference (pp. 124-155). Cham: Springer Nature Switzerland. [Google Scholar] [Crossref]

30. Carrico, A. W., Cherenack, E. M., Rubin, L. H., McIntosh, R., Ghanooni, D., Chavez, J. V., ... & Paul, R. H. (2022). Through the looking-glass: psychoneuroimmunology and the microbiome-gut-brain axis in the modern antiretroviral therapy era. Biopsychosocial Science and Medicine, 84(8), 984-994. [Google Scholar] [Crossref]

31. Stiehl, T. (2023). Multiplicity of time scales in blood cell formation and leukemia: Contributions of computational disease modeling to mechanistic understanding and personalized medicine. In Multiplicity of Time Scales in Complex Systems: Challenges for Sciences and Communication I (pp. 327-400). Cham: Springer International Publishing. [Google Scholar] [Crossref]

32. Zhang, Y. Z., Ma, R. W., Bhandari, S., Xie, J., Zhang, X. Y., Xie, C., ... & Cheng, L. M. (2025). Association between systemic immune inflammation index and adolescent obesity in a cross-sectional analysis. Scientific Reports, 15(1), 6439. [Google Scholar] [Crossref]

33. Cheng, N., Chen, Y., Jin, L., & Chen, L. (2025). Nonlinear association between visceral fat metabolism score and heart failure: insights from LightGBM modeling and SHAP-Driven feature interpretation in NHANES. BMC Medical Informatics and Decision Making, 25(1), 223. [Google Scholar] [Crossref]

34. Matthews, C. (2024). Co-developing a health literacy framework to integrate nutrition into standard care in sickle cell disease (Doctoral dissertation, Anglia Ruskin Research Online (ARRO)). [Google Scholar] [Crossref]

35. Egemba, M., Bolarinwa, D., & Ogundipe, M. (2025). Innovative Public Health Strategies and Care Delivery Models to Enhance Outcomes for People Living with HIV. [Google Scholar] [Crossref]

36. Manyazewal, T., Woldeamanuel, Y., Blumberg, H. M., Fekadu, A., & Marconi, V. C. (2021). The potential use of digital health technologies in the African context: a systematic review of evidence from Ethiopia. NPJ digital medicine, 4(1), 125. [Google Scholar] [Crossref]

37. Oyetunji, I. O. (2022). Nutritional and health status of HIV+ adults stable on HAART attending a healthcare facility in Cape Town, South Africa. [Google Scholar] [Crossref]

38. Nuka, S. T. (2025). Next-Frontier Medical Devices and Embedded Systems: Harnessing Biomedical Engineering, Artificial Intelligence, and Cloud-Powered Big Data Analytics for Smarter Healthcare Solutions. Deep Science Publishing. [Google Scholar] [Crossref]

39. Odubela, O. O., Peer, N., Odunukwe, N. N., Musa, A. Z., Salako, B. L., & Kengne, A. P. (2025). Weight changes among antiretroviral therapy-naïve people living with human immunodeficiency virus in Lagos, Nigeria. Frontiers in Public Health, 13, 1545676. [Google Scholar] [Crossref]

40. Alebel, A., Demant, D., Petrucka, P. M., & Sibbritt, D. (2022). Weight change after antiretroviral therapy initiation among adults living with HIV in Northwest Ethiopia: a longitudinal data analysis. BMJ open, 12(2), e055266. [Google Scholar] [Crossref]

41. Igirikwayo, Z. K., Migisha, R., Mukaga, H., & Kabakyenga, J. (2024). Prescription patterns of antibiotics and associated factors among outpatients diagnosed with respiratory tract infections in Jinja city, Uganda, June 2022–May 2023. BMC Pulmonary Medicine, 24(1), 446. [Google Scholar] [Crossref]

42. Čepukaitytė, G., & Chan, D. (2025). Opportunities arising from the tech revolution. In Early Detection in Alzheimer's Disease (pp. 99-122). Academic Press. [Google Scholar] [Crossref]

43. Atandero, M. O., Fasipe, O. J., Famakin, S. M., & Ogunboye, I. (2025). A cross-sectional survey of comorbidity profile among adult Human Immunodeficiency Virus-infected patients attending a Nigeria medical university teaching hospital campus located in Akure, Ondo State. Archives of Medicine and Health Sciences, 13(1), 9-22. [Google Scholar] [Crossref]

44. Orji, M. L. C., Ifebunandu, N. A., Joe-Akunne, C. I., Chidiebere, M. A., Echefu, S., & Eze, J. N. (2025). Assessment of adequacy and determinants of HIV related knowledge among senior school students in public schools in Abakaliki Southeast Nigeria. Scientific Reports, 15(1), 1254. [Google Scholar] [Crossref]

45. Basti, M., & Madadizadeh, F. (2021). A beginner's guide to sampling methods in medical research. Critical Comments in Biomedicine, 2(2). [Google Scholar] [Crossref]

46. Stuckless, S., & Parfrey, P. S. (2021). Bias in clinical research. In Clinical Epidemiology: Practice and Methods (pp. 17-34). New York, NY: Springer US. [Google Scholar] [Crossref]

47. Pantazis, N., Papastamopoulos, V., Antoniadou, A., Adamis, G., Paparizos, V., Metallidis, S., ... & Touloumi, G. (2022). Changes in body mass index after initiation of antiretroviral treatment: differences by class of core drug. Viruses, 14(8), 1677. [Google Scholar] [Crossref]

48. Ryabokon, O. V., Furyk, O. O., Onishchenko, T. E., & Venytska, H. V. (2022). Infectious diseases: hiv-infection (etiology, epidemiology, clinic, principles of treatment and prevention): Training manual for independent training of 6th year students training for the Master of Medicine and Master of Pediatrics fields. [Google Scholar] [Crossref]

49. Fu, W., Yang, K., Tang, R., Wang, J., Liu, Y., Liu, G., ... & Hong, T. (2025). Effects of time-restricted eating on glycemic control in type 2 diabetes: a 12-week quasi-experimental single-arm study with 1-year follow-up. Clinical Nutrition. [Google Scholar] [Crossref]

50. Fuge, T. (2021). HIV Care Continuum in Prison: Initiation, Adherence and Outcomes of Antiretroviral Therapy Amongst Prisoners in South Ethiopia (Doctoral dissertation, Flinders University, College of Medicine and Public Health.). [Google Scholar] [Crossref]

51. Fâcă, A. I., Udeanu, D. I., Arsene, A. L., Mahler, B., Drăgănescu, D., & Apetroaei, M. M. (2025). Nutritional Deficiencies and Management in Tuberculosis: Pharmacotherapeutic and Clinical Implications. Nutrients, 17(11), 1878. [Google Scholar] [Crossref]

52. Martin, L. (2025). Changes in Vitamin B12 Biomarkers and Plasma Volume in Pregnant and Nonpregnant Females. [Google Scholar] [Crossref]

53. Hands, K., Daru, J., Evans, C., Kotze, A., Lewis, C., Narayan, S., ... & BSH Committee. (2024). Identification and management of preoperative anaemia in adults: A British Society for Haematology Guideline update. British journal of haematology, 205(1), 88-99. [Google Scholar] [Crossref]

54. Park, J., Artin, M. G., Lee, K. E., Pumpalova, Y. S., Ingram, M. A., May, B. L., ... & Tatonetti, N. P. (2022). Deep learning on time series laboratory test results from electronic health records for early detection of pancreatic cancer. Journal of biomedical informatics, 131, 104095. [Google Scholar] [Crossref]

55. Parasvita, M. J. V., Wijaya, V., Budiman, N., Wibowo, L., & Lukito, W. (2025). Estimation of body weight from selected body circumferences in the hospital setting. Clinical Nutrition Open Science, 61, 70-81. [Google Scholar] [Crossref]

56. Agbaje, A. O. (2025). Body mass index triples overweight prevalence in 7600 children compared with waist-to-height ratio: the ALSPAC study. Obesity and Endocrinology, 1(1), wjaf002. [Google Scholar] [Crossref]

57. Rappaport, A. I., Karakochuk, C. D., Hess, S. Y., Whitehead Jr, R. D., Namaste, S. M., Dary, O., ... & Moorthy, D. (2021). Variability in haemoglobin concentration by measurement tool and blood source: an analysis from seven countries. Journal of Clinical Pathology, 74(10), 657-663. [Google Scholar] [Crossref]

58. Yan, Y., Mao, Z., Jia, Q., Zhao, X. J., & Yang, S. H. (2023). Changes in blood pressure, oxygen saturation, hemoglobin concentration, and heart rate among low‐altitude migrants living at high altitude (5380 m) for 360 days. American Journal of Human Biology, 35(9), e23913. [Google Scholar] [Crossref]

59. Zoorob, D., Goldschmidt, K., & Aouthmany, S. (2022). What If Training Programs Affirmed Their Commitment To Resident Wellbeing By Assigning Wellness Associate Program Directors?. North American Proceedings in Gynecology & Obstetrics, 2(2), 1-3. [Google Scholar] [Crossref]

60. Maré, I. A., Kramer, B., Hazelhurst, S., Nhlapho, M. D., Zent, R., Harris, P. A., & Klipin, M. (2022). Electronic data capture system (REDCap) for health care research and training in a resource-constrained environment: technology adoption case study. JMIR Medical Informatics, 10(8), e33402. [Google Scholar] [Crossref]

61. Cheng, A. C., Banasiewicz, M. K., Johnson, J. D., Sulieman, L., Kennedy, N., Delacqua, F., ... & Harris, P. A. (2023). Evaluating automated electronic case report form data entry from electronic health records. Journal of Clinical and Translational Science, 7(1), e29. [Google Scholar] [Crossref]

62. Kassam, N. A., Mwanga, G. A., Yusuph, E. L., Maundi, E. M., Josephat, M., Kulaya, N. B., ... & Ndaro, A. (2024). Performance of Hb HemoCue machine compared to automated hematology analyzer for hemoglobin measurements among adult patients at Kilimanjaro Christian Medical Centre. medRxiv, 2024-12. [Google Scholar] [Crossref]

63. Aulia, K. R., Hendrianingtyas, M., Limijadi, E. K. S., & Pramono, D. (2022). Anthropometric Measurements and Inflammatory Marker in Obese Women. Jurnal Gizi Indonesia Vol, 10(2), 88-94. [Google Scholar] [Crossref]

64. Russo, V., Silverio, A., Scudiero, F., Di Micco, P., & Di Maio, M. (2021). Pre-admission atrial fibrillation in COVID-19 patients: Prevalence and clinical impact. European journal of internal medicine, 88, 133. [Google Scholar] [Crossref]

65. Chen, X., Chen, S., Li, Z., Pan, X., Jia, Y., Hu, Z., ... & Ren, Q. (2022). Correlation of body mass index with clinicopathologic parameters in patients with idiopathic membranous nephropathy. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy, 1897-1909. [Google Scholar] [Crossref]

66. Hillary, R. F., Ng, H. K., McCartney, D. L., Elliott, H. R., Walker, R. M., Campbell, A., ... & Suderman, M. (2024). Blood-based epigenome-wide analyses of chronic low-grade inflammation across diverse population cohorts. Cell Genomics, 4(5). [Google Scholar] [Crossref]

67. O’Shea-Stone, G. P. (2024). INVESTIGATING THE EFFECTS OF CAPTURE AND NUTRITIONAL VARIANCE ON THE METABOLISM OF WILD BIGHORN SHEEP USING QUANTITATIVE 1H NMR (Doctoral dissertation, MONTANA STATE UNIVERSITY Bozeman). [Google Scholar] [Crossref]

68. Tapio, J., Vähänikkilä, H., Kesäniemi, Y. A., Ukkola, O., & Koivunen, P. (2021). Higher hemoglobin levels are an independent risk factor for adverse metabolism and higher mortality in a 20-year follow-up. Scientific Reports, 11(1), 19936. [Google Scholar] [Crossref]

69. Jung, C., Erkens, R., Wischmann, P., Piayda, K., Kelm, M., & Kuhnle, G. (2023). Haemoglobin levels as a predictor for the occurrence of future cardiovascular events in adults–Sex-dependent results from the EPIC trial. European Journal of Internal Medicine, 118, 118-124. [Google Scholar] [Crossref]

70. Hiremath, R. N. (2021). A Prospective Study To Assess The Factors Affecting Nutritional Status Of People Living With Hiv/Aids (Plha) Receiving Anti-Retroviral Therapy (Art) (Doctoral dissertation, BLDE (Deemed to be University)). [Google Scholar] [Crossref]

71. Oliveira, V. H., Webel, A. R., Borsari, A. L., Cárdenas, J. D. G., & Deminice, R. (2023). Health and sociodemographic factors associated with low muscle strength, muscle mass, and physical performance among people living with HIV. AIDS care, 35(12), 1863-1873. [Google Scholar] [Crossref]

72. Hedayanti, N., & Wahyudi, A. (2023). Review of Physiological Aspects of Erythropoie sis: A Narrative Literature Review. Sriwijaya Journal of Internal Medicine, 1(1), 18-24. [Google Scholar] [Crossref]

73. Lacy, S. A. (2021). A Retrospective Chart Review of Patients with Nutritional Deficiencies and Anemia: An Evaluation of Assessment, Diagnosis, and Treatment (Master's thesis, The Ohio State University). [Google Scholar] [Crossref]

74. Werner, E. R. (2022). Evaluation of the Potential for Eggs, Fish, and Meat to Improve Vitamin A, Iron, and Anemia in Young Malawian Children (Doctoral dissertation, University of California, Davis). [Google Scholar] [Crossref]

75. Lauer, J. M., Kirby, M. A., Muhihi, A., Ulenga, N., Aboud, S., Liu, E., ... & Duggan, C. P. (2024). Effects of Vitamin D-3 Supplementation During Pregnancy and Lactation on Maternal and Infant Biomarkers of Environmental Enteric Dysfunction, Systemic Inflammation, and Growth: A Secondary Analysis of a Randomized Controlled Trial. The Journal of Nutrition, 154(11), 3400-3406. [Google Scholar] [Crossref]

76. Okoka, E. M., Kuyebi, M. A., Oyadiran, O. T., Okusanya, T. R., Onaku, E., Omotayo, M. O., & Abioye, A. I. (2025). Effect of Micronutrients on HIV-Related Clinical Outcomes Among Adults Living With HIV on Antiretroviral Therapy: Systematic Review and Meta-analysis. Nutrition Reviews, 83(7), e1488-e1503. [Google Scholar] [Crossref]

77. Mehra, V., Sharma, A., Kaur, H., & Chakraborty, S. A Comprehensive Review of Anemia: Characterization, Challenges and Management. [Google Scholar] [Crossref]

78. Mitkin, N. A. (2025). Associations of Alcohol with Body Composition, Physical Function and Mortality in Russia: The Know Your Heart Study. [Google Scholar] [Crossref]

79. Reddy, K. (2025). Disparities in Clinical Trial Representation: Bioethical & Human Rights Violations Against the Global Burden of Disease and Gender Equity (Master's thesis, Yale University). [Google Scholar] [Crossref]

80. Munro, M. G., Mast, A. E., Powers, J. M., Kouides, P. A., O’Brien, S. H., Richards, T., ... & Levy, B. S. (2023). The relationship between heavy menstrual bleeding, iron deficiency, and iron deficiency anemia. American journal of obstetrics and gynecology, 229(1), 1-9. [Google Scholar] [Crossref]

81. Maina Mwaura, F. Interplay Between Infant Nutrition and Malaria Susceptibility in West Africa: Socioeconomic, Environmental, and Cultural Perspectives. [Google Scholar] [Crossref]

82. Rodriguez-Diaz, C. E., Davis, W., Ellis, M. V., Cameron, M. S., Donastorg, Y., Bowleg, L., ... & Kerrigan, D. (2021). Disrupting the systems: opportunities to enhance methodological approaches to address socio-structural determinants of HIV and end the epidemic through effective community engagement. AIDS and Behavior, 25(Suppl 2), 225-231. [Google Scholar] [Crossref]

83. Daif, N., Di Nunno, F., Granata, F., Difi, S., Kisi, O., Heddam, S., ... & Zounemat-Kermani, M. (2025). Forecasting maximal and minimal air temperatures using explainable machine learning: Shapley additive explanation versus local interpretable model-agnostic explanations. Stochastic Environmental Research and Risk Assessment, 39(6), 2551-2581. [Google Scholar] [Crossref]

84. Uyoga, S., George, E. C., Bates, I., Olupot‐Olupot, P., Chimalizeni, Y., Molyneux, E. M., & Maitland, K. (2021). Point‐of‐care haemoglobin testing in African hospitals: a neglected essential diagnostic test. British journal of haematology, 193(5), 894-901. [Google Scholar] [Crossref]

85. Butler, C. C., Hobbs, F. R., Gbinigie, O. A., Rahman, N. M., Hayward, G., Richards, D. B., ... & Zafar, A. (2023). Molnupiravir plus usual care versus usual care alone as early treatment for adults with COVID-19 at increased risk of adverse outcomes (PANORAMIC): an open-label, platform-adaptive randomised controlled trial. The Lancet, 401(10373), 281-293. [Google Scholar] [Crossref]

• Tribal Child Nutrition and Health in District of Sundargarh: A Public Health Review of ICDS Intervention
• Knowledge, Attitudes and Practices Towards Prostate Cancer Screening Amongst Men Aged 40-60 Years in The Buea Health District: A Cross-Sectional Study
• Compliance with JCI Protocols: A Focus on Employee Safety
• Influence and Involvement of Teachers in Menstrual Hygiene Management of Female Secondary School Students in Kogi State, Nigeria
• A Critical Evaluation of Ayushman Bharat Pradhan Mantri Jan Arogya Yojana in Bihar