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Radinka Journal of Health Science
Published by Radinka Jaya Utama Publisher
ISSN : -     EISSN : 30257751     DOI : https://doi.org/10.56778/RJHS
Core Subject : Health,
Dentistry Health Professions Medicine & Pharmacology Nursing Public Health
The Radinka Journal of Health Science (RJHS) accepts manuscripts in the fields of : 1. Medical laboratory engineering 2. Health information management 3. Pharmacy 4. Midwifery 5. Occupational health and safety 6. Nursing 7. Physiotherapy 8. Health promotion 9. Public health 10. Medicine (miscellaneous) 11. Environmental health 12. Dental health 13. Dental engineering 14. Radiology 15. Nutrition 16. Sanitation 17. Epidemiological supervision 18. Health psychology 19. Health technology 20. Health law 21. Hospital management, etc.
Arjuna Subject : Profesi Kesehatan - Menejmen Informasi Kesehatan
Articles 62 Documents
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AI-Enhanced Flood Prediction and Environment Health Risk Communication: A Counselling Framework for Sustainable Development in the Niger Delta of Nigeria Nathan Udoinyang; Edna Abibetu ABIDDE; Enebi AVWORO; Osiokor Onoriode ALEXANDER
RADINKA JOURNAL OF HEALTH SCIENCE Vol. 3 No. 4 (2026): Radinka Journal of Heatlh Science (RJHS)
Publisher : RADINKA JAYA UTAMA PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56778/rjhs.v3i4.713

Abstract

This study examines the integration of artificial intelligence (AI) in flood prediction and counselling-based environmental health risk communication in the Niger Delta region of Nigeria. The aim is to develop a comprehensive framework that enhances disaster preparedness and supports sustainable development. A mixed-method research design was employed, involving 450 respondents selected from Delta, Bayelsa, and Rivers States. Data were collected through structured questionnaires and interviews and then analysed using descriptive statistics, thematic analysis, and multiple regression techniques. The findings reveal that while flood risk awareness is high among residents, awareness of AI-based prediction systems and communication effectiveness remain moderate. Thematic results indicate that mistrust in government communication and delays in information dissemination are key barriers to effective risk communication and the adoption of AI-based prediction systems among residents. Regression analysis shows that AI prediction systems (β = 0.42) and counselling communication (β = 0.37) significantly improve environmental health risk awareness, leading to rejection of the null hypothesis. The study concludes that integrating AI technologies with counselling frameworks enhances risk communication, promotes behavioural change, and improves disaster preparedness. It recommends increased investment in AI systems, the incorporation of counselling services in disaster management, and the development of trust-based communication strategies. This integrated approach is essential for achieving sustainable development goals in flood-prone regions.
Urban Land Use and Environmental Health Risks: Assessing Human Exposure to Microplastic Pollution in The River Benue Watershed, Makurdi, Nigeria Odediran Bukola Sunday
RADINKA JOURNAL OF HEALTH SCIENCE Vol. 3 No. 4 (2026): Radinka Journal of Heatlh Science (RJHS)
Publisher : RADINKA JAYA UTAMA PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56778/rjhs.v3i4.720

Abstract

Rapid urban expansion and unregulated land use change in sub-Saharan African cities intensify the discharge of microplastic contaminants into inland freshwater bodies, leading to human health risks. The River Benue watershed in Makurdi, Nigeria is under mounting pressure from agricultural runoff, industrial effluents and inadequate solid-waste management, yet baseline data on microplastic contamination and associated health risk remain scarce. This study quantifies and characterises microplastic concentrations in surface water and sediments of the River Benue across sites stratified by dominant land use. Water and sediment samples were collected in triplicate from six sites representing urban commercial, peri-urban agricultural and residential land use zones along a 14 km transect of the river during dry and wet seasons (January–June 2024). Microplastics were isolated via density separation and vacuum filtration, characterised morphologically under stereo microscopy, and polymer-typed by micro-Fourier Transform Infrared Spectroscopy (μ-FTIR). Estimated Daily Intake (EDI), Hazard Quotient (HQ), and Monte Carlo simulation were applied for health risk modelling. Microplastic concentrations ranged from 120 ± 18 to 406 ± 43 particles/L in surface water and from 284 ± 31 to 1,142 ± 98 particles/kg dry weight in sediment. Fibres (54.7%) and fragments (26.3%) dominated morphologically; polyethylene terephthalate (PET, 31.2%), polypropylene (PP, 22.8%), and polyethylene (PE, 19.5%) were the most abundant polymers. Concentrations were higher at commercial sites and correlated positively with population density and distance from formal waste disposal infrastructure. The mean EDI for adults via water ingestion was 1.87 × 10⁻² mg/kg-bw/day. Monte Carlo-derived HQ values ranged from 0.83 to 2.14, indicating sub-populations near high-load sites may face non-trivial health risk. Urban land use intensity is a primary determinant of microplastic loading in the River Benue, with health risk estimates exceeding safety thresholds for vulnerable sub-populations. Targeted land use regulation, improved solid-waste infrastructure, and systematic riverine monitoring are urgently needed in Makurdi and comparable Nigerian cities

Page 7 of 7 | Total Record : 62

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