Analyzing Health Disparities through Epidemiological Data: A Conceptual Framework for Evidence-Based Solutions
DOI:
https://doi.org/10.32628/CSEIT25112852Keywords:
Health disparities, Epidemiological data, Social determinants of health, Evidence-based solutions, Health equity, Policy reformAbstract
Health disparities persist as a significant global challenge, with unequal health outcomes rooted in social, economic, and structural factors. This paper analyzes these disparities through a conceptual framework informed by epidemiological data, emphasizing the role of evidence-based strategies in addressing inequities. Key insights from epidemiological research highlight disparities across race, gender, socioeconomic status, and geography, underscoring the need for targeted interventions and systemic reforms. Evidence-based solutions are proposed, including public health programs, community engagement, and policy changes addressing social determinants of health. Challenges such as resource constraints and resistance to systemic change are acknowledged alongside technological innovations and multi-sectoral collaboration opportunities. This study concludes by advocating for coordinated efforts among policymakers, researchers, and healthcare practitioners to ensure equitable health outcomes for all populations, emphasizing the critical role of data in shaping effective and sustainable solutions.
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Adelodun, M. O., & Anyanwu, E. C. (2024a). Comprehensive risk management and safety strategies in radiation use in medical imaging.
Adelodun, M. O., & Anyanwu, E. C. (2024b). A critical review of public health policies for radiation protection and safety.
Adelodun, M. O., & Anyanwu, E. C. (2024c). Environmental and patient safety: Advances in radiological techniques to reduce radiation exposure.
Adkins‐Jackson, P. B., George, K. M., Besser, L. M., Hyun, J., Lamar, M., Hill‐Jarrett, T. G., . . . Cicero, E. C. (2023). The structural and social determinants of Alzheimer's disease related dementias. Alzheimer's & Dementia, 19(7), 3171-3185.
Aenishaenslin, C., Häsler, B., Ravel, A., Parmley, E. J., Mediouni, S., Bennani, H., . . . Buckeridge, D. L. (2021). Evaluating the integration of One Health in surveillance systems for antimicrobial use and resistance: a conceptual framework. Frontiers in veterinary science, 8, 611931.
Breilh, J. (2021). Critical epidemiology and the people's health: Oxford University Press, USA.
Bridges, K. M. (2020). Racial disparities in maternal mortality. NYUL Rev., 95, 1229.
Diez Roux, A. V. (2022). Social epidemiology: past, present, and future. Annual review of public health, 43(1), 79-98.
Ehidiamen, A. J., & Oladapo, O. O. (2024a). Optimizing contract negotiations in clinical research: Legal strategies for safeguarding sponsors, vendors, and institutions in complex trial environments. World Journal of Biology Pharmacy and Health Sciences, 20(1), 335-348. Retrieved from https://doi.org/10.30574/wjbphs.2024.20.1.0790
Ehidiamen, A. J., & Oladapo, O. O. (2024b). The role of electronic data capture systems in clinical trials: Streamlining data integrity and improving compliance with FDA and ICH/GCP guidelines.
Epstein, W. N. (2022). The health equity mandate. Journal of Law and the Biosciences, 9(1), lsab030.
Golden, T. L., & Wendel, M. L. (2020). Public health's next step in advancing equity: re-evaluating epistemological assumptions to move social determinants from theory to practice. Frontiers in public health, 8, 131.
Hunt, J. (2021). Maternal mortality among black women in the United States. Ballard Brief, 2021(2), 6.
Javed, Z., Haisum Maqsood, M., Yahya, T., Amin, Z., Acquah, I., Valero-Elizondo, J., . . . Daffin, M. A. (2022). Race, racism, and cardiovascular health: applying a social determinants of health framework to racial/ethnic disparities in cardiovascular disease. Circulation: Cardiovascular Quality and Outcomes, 15(1), e007917.
Jimoh Amzat, K. A., & Muchabveyo, B. (2023). Social Determinants of Health in Africa. The Oxford Handbook of the Sociology of Africa, 229.
Johnson, O. B., Olamijuwon, J., Cadet, E., Osundare, O. S., & Ekpobimi, H. O. Optimizing Predictive Trade Models through Advanced Algorithm Development for Cost-Efficient Infrastructure.
Johnson, O. B., Weldegeorgise, Y. W., Cadet, E., Osundare, O. S., & Ekpobimi, H. O. Developing advanced predictive modeling techniques for optimizing business operations and reducing costs.
Kelvin-Agwu, M. C., Adelodun, M. O., Igwama, G. T., & Anyanwu, E. C. (2024a). Advancements in biomedical device implants: A comprehensive review of current technologies.
Kelvin-Agwu, M. C., Adelodun, M. O., Igwama, G. T., & Anyanwu, E. C. (2024b). Strategies For Optimizing The Management Of Medical Equipment In Large Healthcare Institutions. Strategies, 20(9), 162-170.
Lobanov-Rostovsky, S., He, Q., Chen, Y., Liu, Y., Wu, Y., Liu, Y., . . . Hemmings, N. (2023). Growing old in China in socioeconomic and epidemiological context: systematic review of social care policy for older people. BMC public health, 23(1), 1272.
Mackey, K., Ayers, C. K., Kondo, K. K., Saha, S., Advani, S. M., Young, S., . . . Veazie, S. (2021). Racial and ethnic disparities in COVID-19–related infections, hospitalizations, and deaths: a systematic review. Annals of internal medicine, 174(3), 362-373.
Magesh, S., John, D., Li, W. T., Li, Y., Mattingly-App, A., Jain, S., . . . Ongkeko, W. M. (2021). Disparities in COVID-19 outcomes by race, ethnicity, and socioeconomic status: a systematic review and meta-analysis. JAMA network open, 4(11), e2134147-e2134147.
Mansour, A., Bentley, R., Baker, E., Li, A., Martino, E., Clair, A., . . . Phibbs, P. (2022). Housing and health: an updated glossary. J Epidemiol Community Health, 76(9), 833-838.
Mbunge, E., Fashoto, S. G., Akinnuwesi, B. A., Metfula, A. S., Manyatsi, J. S., Sanni, S. A., . . . Mnisi, P. M. (2024). Machine Learning Approaches for Predicting Individual’s Financial Inclusion Status with Imbalanced Dataset. Paper presented at the Computer Science On-line Conference.
Morgenstern, J. D., Rosella, L. C., Costa, A. P., de Souza, R. J., & Anderson, L. N. (2021). Perspective: Big data and machine learning could help advance nutritional epidemiology. Advances in Nutrition, 12(3), 621-631.
Ojukwu, P. U., Cadet, E., Osundare, O. S., Fakeyede, O. G., Ige, A. B., & Uzoka, A. Advancing Green Bonds through FinTech Innovations: A Conceptual Insight into Opportunities and Challenges.
Omotayo, O., Maduka, C. P., Muonde, M., Olorunsogo, T. O., & Ogugua, J. O. (2024). The rise of non-communicable diseases: a global health review of challenges and prevention strategies. International Medical Science Research Journal, 4(1), 74-88.
Osuh, M. E. (2022). Prevalence and determinants of oral diseases and oral health care needs in slums: a comparative study with non-slum urban settings in Nigeria. University of Warwick,
Patterson, E. J., Becker, A., & Baluran, D. A. (2022). Gendered racism on the body: an intersectional approach to maternal mortality in the United States. Population Research and Policy Review, 41(3), 1261-1294.
Perry, M. J., Arrington, S., Freisthler, M. S., Ibe, I. N., McCray, N. L., Neumann, L. M., . . . Trejo Rosas, B. M. (2021). Pervasive structural racism in environmental epidemiology. Environmental Health, 20, 1-13.
Ponsonby, A.-L. (2021). Reflection on modern methods: building causal evidence within high-dimensional molecular epidemiological studies of moderate size. International Journal of Epidemiology, 50(3), 1016-1029.
Rivera, M. P., Katki, H. A., Tanner, N. T., Triplette, M., Sakoda, L. C., Wiener, R. S., . . . Fathi, J. T. (2020). Addressing disparities in lung cancer screening eligibility and healthcare access. An official American Thoracic Society statement. American journal of respiratory and critical care medicine, 202(7), e95-e112.
Segun-Falade, O. D., Osundare, O. S., Kedi, W. E., Okeleke, P. A., Ijomah, T. I., & Abdul-Azeez, O. Y. (2024). Utilizing machine learning algorithms to enhance predictive analytics in customer behavior studies.
Shittu, R. A., Ehidiamen, A. J., Ojo, O. O., & Christophe, S. J. (2024). The role of business intelligence tools in improving healthcare patient outcomes and operations.
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