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Cardiovascular disease behavioural risk factors in rural interventions: cross-sectional study
This study aims to (1) assess the distribution of variables within the population and the prevalence of cardiovascular disease (CVD) behavioural risk factors in patients, (2) identify target risk factor(s) for behaviour modification intervention, and (3) develop an analytical model to define cluster...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10435574/ https://www.ncbi.nlm.nih.gov/pubmed/37591952 http://dx.doi.org/10.1038/s41598-023-39451-5 |
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author | Akinosun, Adewale Samuel Kamya, Sylvia Watt, Jonathan Johnston, William Leslie, Stephen J. Grindle, Mark |
author_facet | Akinosun, Adewale Samuel Kamya, Sylvia Watt, Jonathan Johnston, William Leslie, Stephen J. Grindle, Mark |
author_sort | Akinosun, Adewale Samuel |
collection | PubMed |
description | This study aims to (1) assess the distribution of variables within the population and the prevalence of cardiovascular disease (CVD) behavioural risk factors in patients, (2) identify target risk factor(s) for behaviour modification intervention, and (3) develop an analytical model to define cluster(s) of risk factors which could help make any generic intervention more targeted to the local patient population. Study patients with at least one CVD behavioural risk factor living in a rural region of the Scottish Highlands. The study used the STROBE methodology for cross-sectional studies. Demographic and clinical data of patients (n = 2025) in NHS Highlands hospital were collected at the point of admission for PCI between 04.01.2016 and 31.12.2019. Collected data distributions were analysed by CVD behavioural risk factors for prevalence, associations, and direction of associations. Cluster definition was measured by assignment of a unit score each for the overall level of prevalence and significance of associations, and general logistics modelling for direction and significance of the risk. The mean (SD) age was 69.47(± 10.93) years [95% CI (68.99–69.94)]. The key risk factors were hyperlipidaemia, hypertension, and elevated body mass index (BMI). Approximately 40% of the population have multiple risk factor counts of two. Analytical measures revealed a population risk factor cluster with elevated BMI [77.5% (1570/2025)] that is mostly either hyperlipidaemic [9.43%, co-eff. (17), P = 0.007] or hypertensive [22.72%, co-eff. (17), P = 0.99] as key risk factor clusters. Carefully modelled analyses revealed clustered risk associated with elevated BMI. This information would support a strategy for targeting risk factor clusters in novel interventions to improve implementation efficiency. Exposure to and outcome of an elevated BMI is linked more to the population’s socio-economic outcomes rather than to regional rurality or urbanity. |
format | Online Article Text |
id | pubmed-10435574 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-104355742023-08-19 Cardiovascular disease behavioural risk factors in rural interventions: cross-sectional study Akinosun, Adewale Samuel Kamya, Sylvia Watt, Jonathan Johnston, William Leslie, Stephen J. Grindle, Mark Sci Rep Article This study aims to (1) assess the distribution of variables within the population and the prevalence of cardiovascular disease (CVD) behavioural risk factors in patients, (2) identify target risk factor(s) for behaviour modification intervention, and (3) develop an analytical model to define cluster(s) of risk factors which could help make any generic intervention more targeted to the local patient population. Study patients with at least one CVD behavioural risk factor living in a rural region of the Scottish Highlands. The study used the STROBE methodology for cross-sectional studies. Demographic and clinical data of patients (n = 2025) in NHS Highlands hospital were collected at the point of admission for PCI between 04.01.2016 and 31.12.2019. Collected data distributions were analysed by CVD behavioural risk factors for prevalence, associations, and direction of associations. Cluster definition was measured by assignment of a unit score each for the overall level of prevalence and significance of associations, and general logistics modelling for direction and significance of the risk. The mean (SD) age was 69.47(± 10.93) years [95% CI (68.99–69.94)]. The key risk factors were hyperlipidaemia, hypertension, and elevated body mass index (BMI). Approximately 40% of the population have multiple risk factor counts of two. Analytical measures revealed a population risk factor cluster with elevated BMI [77.5% (1570/2025)] that is mostly either hyperlipidaemic [9.43%, co-eff. (17), P = 0.007] or hypertensive [22.72%, co-eff. (17), P = 0.99] as key risk factor clusters. Carefully modelled analyses revealed clustered risk associated with elevated BMI. This information would support a strategy for targeting risk factor clusters in novel interventions to improve implementation efficiency. Exposure to and outcome of an elevated BMI is linked more to the population’s socio-economic outcomes rather than to regional rurality or urbanity. Nature Publishing Group UK 2023-08-17 /pmc/articles/PMC10435574/ /pubmed/37591952 http://dx.doi.org/10.1038/s41598-023-39451-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Akinosun, Adewale Samuel Kamya, Sylvia Watt, Jonathan Johnston, William Leslie, Stephen J. Grindle, Mark Cardiovascular disease behavioural risk factors in rural interventions: cross-sectional study |
title | Cardiovascular disease behavioural risk factors in rural interventions: cross-sectional study |
title_full | Cardiovascular disease behavioural risk factors in rural interventions: cross-sectional study |
title_fullStr | Cardiovascular disease behavioural risk factors in rural interventions: cross-sectional study |
title_full_unstemmed | Cardiovascular disease behavioural risk factors in rural interventions: cross-sectional study |
title_short | Cardiovascular disease behavioural risk factors in rural interventions: cross-sectional study |
title_sort | cardiovascular disease behavioural risk factors in rural interventions: cross-sectional study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10435574/ https://www.ncbi.nlm.nih.gov/pubmed/37591952 http://dx.doi.org/10.1038/s41598-023-39451-5 |
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