Predictors of diagnosed cardiovascular diseases and their spatial heterogeneity in Lagos State, Nigeria
Cardiovascular diseases (CVDs) persist as the foremost global cause of death despite persistent efforts to comprehend the risk factors associated with them. Low- and middle-income countries (LMICs) are disproportionately affected, bearing a high burden of CVD morbidity and mortality. Nevertheless, t...
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
De Gruyter
2024-01-01
|
Series: | Open Health |
Subjects: | |
Online Access: | https://doi.org/10.1515/ohe-2023-0018 |
_version_ | 1797294629081579520 |
---|---|
author | Addie Oluwaseun John Taiwo Olalekan |
author_facet | Addie Oluwaseun John Taiwo Olalekan |
author_sort | Addie Oluwaseun |
collection | DOAJ |
description | Cardiovascular diseases (CVDs) persist as the foremost global cause of death despite persistent efforts to comprehend the risk factors associated with them. Low- and middle-income countries (LMICs) are disproportionately affected, bearing a high burden of CVD morbidity and mortality. Nevertheless, the intricate socio-spatial landscape that could yield new insights into CVD incidence within LMICs like Nigeria has not received sufficient attention. This study aimed to determine the predictors of CVDs in a megacity in one of the LMICs and investigate their spatial heterogeneity. The study acquired and appropriately geocoded hospital records of patients clinically diagnosed with CVDs between 2008 and 2018 from a tertiary healthcare facility. Stepwise regression and geographically weighted regression were employed to identify predictors of CVDs and investigate their patterns. The study’s findings revealed that gender emerged as the primary predictor of diagnosed CVDs. Consequently, the study underscores the importance of focusing on the female population in efforts to control and prevent CVDs while advocating for the formulation and implementation of spatially sensitive policies and interventions. |
first_indexed | 2024-03-07T21:33:56Z |
format | Article |
id | doaj.art-b08f93f1ea3d4c7fac00496bbd7ce217 |
institution | Directory Open Access Journal |
issn | 2544-9826 |
language | English |
last_indexed | 2024-03-07T21:33:56Z |
publishDate | 2024-01-01 |
publisher | De Gruyter |
record_format | Article |
series | Open Health |
spelling | doaj.art-b08f93f1ea3d4c7fac00496bbd7ce2172024-02-26T14:28:49ZengDe GruyterOpen Health2544-98262024-01-0151132410.1515/ohe-2023-0018Predictors of diagnosed cardiovascular diseases and their spatial heterogeneity in Lagos State, NigeriaAddie Oluwaseun0John Taiwo Olalekan1Department of Geography, University of Ibadan, Ibadan, NigeriaDepartment of Geography, University of Ibadan, Ibadan, NigeriaCardiovascular diseases (CVDs) persist as the foremost global cause of death despite persistent efforts to comprehend the risk factors associated with them. Low- and middle-income countries (LMICs) are disproportionately affected, bearing a high burden of CVD morbidity and mortality. Nevertheless, the intricate socio-spatial landscape that could yield new insights into CVD incidence within LMICs like Nigeria has not received sufficient attention. This study aimed to determine the predictors of CVDs in a megacity in one of the LMICs and investigate their spatial heterogeneity. The study acquired and appropriately geocoded hospital records of patients clinically diagnosed with CVDs between 2008 and 2018 from a tertiary healthcare facility. Stepwise regression and geographically weighted regression were employed to identify predictors of CVDs and investigate their patterns. The study’s findings revealed that gender emerged as the primary predictor of diagnosed CVDs. Consequently, the study underscores the importance of focusing on the female population in efforts to control and prevent CVDs while advocating for the formulation and implementation of spatially sensitive policies and interventions.https://doi.org/10.1515/ohe-2023-0018diagnosed cvdgeographically weighted regressionspatial heterogeneity |
spellingShingle | Addie Oluwaseun John Taiwo Olalekan Predictors of diagnosed cardiovascular diseases and their spatial heterogeneity in Lagos State, Nigeria Open Health diagnosed cvd geographically weighted regression spatial heterogeneity |
title | Predictors of diagnosed cardiovascular diseases and their spatial heterogeneity in Lagos State, Nigeria |
title_full | Predictors of diagnosed cardiovascular diseases and their spatial heterogeneity in Lagos State, Nigeria |
title_fullStr | Predictors of diagnosed cardiovascular diseases and their spatial heterogeneity in Lagos State, Nigeria |
title_full_unstemmed | Predictors of diagnosed cardiovascular diseases and their spatial heterogeneity in Lagos State, Nigeria |
title_short | Predictors of diagnosed cardiovascular diseases and their spatial heterogeneity in Lagos State, Nigeria |
title_sort | predictors of diagnosed cardiovascular diseases and their spatial heterogeneity in lagos state nigeria |
topic | diagnosed cvd geographically weighted regression spatial heterogeneity |
url | https://doi.org/10.1515/ohe-2023-0018 |
work_keys_str_mv | AT addieoluwaseun predictorsofdiagnosedcardiovasculardiseasesandtheirspatialheterogeneityinlagosstatenigeria AT johntaiwoolalekan predictorsofdiagnosedcardiovasculardiseasesandtheirspatialheterogeneityinlagosstatenigeria |