Evidence map›Paper›PMID 39910619›Full record

ArticleBMC public health2025

Geo-behavioural predictors of diagnosed hypertension in Igbo Ora Area, Oyo State, Nigeria.

Olalekan J Taiwo, Joshua O Akinyemi, Ayodeji Adebayo, Oluwafemi A Popoola, Rufus O Akinyemi, Onoja M Akpa, Paul Olowoyo, Akinkunmi P Okekunle, Ezinne O Uvere, Omotolani Titilayo Ajala and 10 more

Abstract read
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors.

Olalekan J TaiwoDepartment of Geography, Faculty of the Social Sciences, University of Ibadan, Ibadan, Oyo State, Nigeria.
Joshua O AkinyemiDepartment of Epidemiology and Medical Statistics, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.
Ayodeji AdebayoDepartment of Community Medicine, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.
Oluwafemi A PopoolaDepartment of Community Medicine, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.
Rufus O AkinyemiNeuroscience and Ageing Research Unit, IAMRAT, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.
Onoja M AkpaDepartment of Epidemiology and Medical Statistics, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.
Paul OlowoyoDepartment of Medicine, Afe Babalola University, Ado Ekiti, Nigeria.
Akinkunmi P OkekunleDepartment of Medicine, College of Medicine, University of Ibadan, and University College Hospital, Ibadan, Oyo State, Nigeria.
Ezinne O UvereCenter for Genomic and Precision Medicine, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.
Omotolani Titilayo AjalaCenter for Genomic and Precision Medicine, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.
Chukwuemeka NwimoCenter for Genomic and Precision Medicine, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.
Olayinka J AdebajoCenter for Genomic and Precision Medicine, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.
Adewale E AyodeleCenter for Genomic and Precision Medicine, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.
Ayodeji SalamiDepartment of Pathology, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.
Oyedunni S ArulogunDepartment of Health Promotion and Education, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.
Olanrewaju OlaniyanDepartment of Economics, Faculty of Social Sciences, University of Ibadan, Ibadan, Oyo State, Nigeria.
Richard W WalkerPopulation Health Sciences Institute, Newcastle University, Newcastle, UK.
Carolyn JenkinsCollege of Nursing, Medical University of South Carolina, Charleston, USA.
Bruce OvbiageleNorthern California Institute for Research and Education, University of California, San Francisco, USA.
Mayowa OwolabiCenter for Genomic and Precision Medicine, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria. mayowaowolabi@yahoo.com.

Funding

Stroke Investigative Research & Educational Network (SIREN)U54HG007479 · NHGRI · COLLEGE OF MEDICINE, UNIVERSITY OF IBADAN · PI OVBIAGELE, BRUCE, OWOLABI, MAYOWA OJO · 2013 to 2017
$4.2M
African Rigorous Innovative Stroke Epidemiological Surveillance (ARISES)R01NS115944 · NINDS · COLLEGE OF MEDICINE, UNIVERSITY OF IBADAN · PI OVBIAGELE, BRUCE, OWOLABI, MAYOWA OJO · 2020 to 2025
$2.2M
Systematic Investigation of Blacks with Stroke - Genomics (SIBS-Genomics) StudyR01NS107900 · NINDS · COLLEGE OF MEDICINE, UNIVERSITY OF IBADAN · PI OVBIAGELE, BRUCE, OWOLABI, MAYOWA OJO · 2018 to 2021
$1.8M
Training Africans to Lead and Execute Neurological Trials & Studies (TALENTS)D43TW012030 · FIC · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI OVBIAGELE, BRUCE · 2021 to 2025
$1.2M
Growing Data-science Research in Africa to Stimulate Progress (GRASP)UE5HL172183 · NHLBI · COLLEGE OF MEDICINE, UNIVERSITY OF IBADAN · PI FATUMO, SEGUN, OVBIAGELE, BRUCE · 2023 to 2025
$568k
ARISES R01NS115944-01FIC NIH HHS D43 TW012030NHGRI NIH HHS U54 HG007479NHLBI NIH HHS UE5 HL172183NINDS NIH HHS R01 NS107900NINDS NIH HHS R01 NS115944SIREN U54HG007479
6 · The paper itself

Abstract

Diagnosed hypertension stands out as a prominent global cause of mortality, prompting recent efforts to understand not only treatment options but also determinants across diverse age and occupational groups. However, the literature on the impact of environmental factors on diagnosed hypertension is limited, especially in rural areas with restricted access to health infrastructure. Geographical determinants research has often focused on spatial variations across different units, potentially masking individual environmental contributions. Data on diagnosed hypertension patients and their behaviours were gathered during the ARISE project, complemented by geographical data (elevation, vegetation, road network, population density, and nighttime light exposure) from secondary sources. Spatial patterns were analyzed using the Nearest Neighbour Statistic, Ripley K Function, and Kernel Density Estimation, while Binomial logistic regression identified predictors. Diagnosed hypertension patients exhibit spatial clustering, and are mainly comprised of elderly individuals, residing closer to roads, at higher elevations, in areas with higher population distribution, and with little or no green vegetation. Socio-economic, health-related, behavioural, and environmental factors collectively drive diagnosed hypertension. Spatial clustering of diagnosed hypertension in the Igbo Ora community is localized, indicating potential spatial factors influencing its prevalence. Beyond identified behavioural and medical history factors, geographical elements like nighttime light exposure and normalized vegetation index contribute to the observed clustering. Understanding these dynamics is crucial for targeted interventions in the community.

Indexed as

HypertensionAdultAgedFemaleHumansMaleMiddle AgedNigeriaRisk FactorsRural PopulationSocioeconomic FactorsSpatial AnalysisDiagnosed hypertensionNighttime lightNormalised difference vegetation index

Identifiers

PMID39910619
PMCPMC11796143

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.