Community-Based Approaches to Diabetes Screening: A Sustainable Model for Rural Nigeria

Diabetes mellitus, a rapidly increasing chronic non-communicable disease, poses a significant public health challenge globally, particularly in low- and middle-income countries (LMICs) like Nigeria. In rural areas of Nigeria, where access to healthcare services is limited, many individuals with diabetes remain undiagnosed, leading to preventable complications and premature death. Community-based diabetes screening offers a sustainable solution by decentralizing healthcare services and engaging local resources such as community health workers and volunteers. This model overcomes geographical, financial, and sociocultural barriers to early diagnosis and management. This review evaluates the effectiveness and feasibility of community-based diabetes screening in rural Nigeria, examining its impact on awareness, early detection, and health outcomes. The review also explores challenges such as funding constraints, cultural stigma, and the need for local capacity-building and offers recommendations for improving the sustainability and scalability of these initiatives. By integrating community-based approaches into the primary healthcare system, Nigeria can improve access to early diabetes diagnosis and reduce the burden of this growing public health concern. Keywords: Diabetes screening, community-based healthcare, rural Nigeria, mobile health.

Authors

Publication Details

Journal
RESEARCH INVENTION JOURNAL OF RESEARCH IN MEDICAL SCIENCES
Published
2025-07-21
DOI
https://doi.org/10.59298/rijrms/2025/436569
Citations
1
Primary Topic
Global Public Health Policies and Epidemiology
Type
article
Field-Weighted Citation Impact
2.76
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Community-Based Approaches to Diabetes Screening: A Sustainable Model for Rural Nigeria

M. J.
1 citations
RESEARCH INVENTION JOURNAL OF RESEARCH IN MEDICAL SCIENCES
Global Public Health Policies and Epidemiology
2.76
article

Community-Based Approaches to Diabetes Screening: A Sustainable Model for Rural Nigeria

M. J.
article en
1 citations

Abstract

Diabetes mellitus, a rapidly increasing chronic non-communicable disease, poses a significant public health challenge globally, particularly in low- and middle-income countries (LMICs) like Nigeria. In rural areas of Nigeria, where access to healthcare services is limited, many individuals with diabetes remain undiagnosed, leading to preventable complications and premature death. Community-based diabetes screening offers a sustainable solution by decentralizing healthcare services and engaging local resources such as community health workers and volunteers. This model overcomes geographical, financial, and sociocultural barriers to early diagnosis and management. This review evaluates the effectiveness and feasibility of community-based diabetes screening in rural Nigeria, examining its impact on awareness, early detection, and health outcomes. The review also explores challenges such as funding constraints, cultural stigma, and the need for local capacity-building and offers recommendations for improving the sustainability and scalability of these initiatives. By integrating community-based approaches into the primary healthcare system, Nigeria can improve access to early diabetes diagnosis and reduce the burden of this growing public health concern. Keywords: Diabetes screening, community-based healthcare, rural Nigeria, mobile health.

RESEARCH INVENTION JOURNAL OF RESEARCH IN MEDICAL SCIENCESVol. 4(3)
Openalex Percentile: Top 9%
Global Public Health Policies and Epidemiology
2.76
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.