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Cross-sectional analysis of factors associated with medication adherence in western Kenya
OBJECTIVES: Poor medication adherence in low-income and middle-income countries is a major cause of suboptimal hypertension and diabetes control. We aimed to identify key factors associated with medication adherence in western Kenya, with a focus on cost-related and economic wealth factors. SETTING:...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10481848/ https://www.ncbi.nlm.nih.gov/pubmed/37669842 http://dx.doi.org/10.1136/bmjopen-2023-072358 |
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author | Gala, Pooja Kamano, Jemima H Vazquez Sanchez, Manuel Mugo, Richard Orango, Vitalis Pastakia, Sonak Horowitz, Carol Hogan, Joseph W Vedanthan, Rajesh |
author_facet | Gala, Pooja Kamano, Jemima H Vazquez Sanchez, Manuel Mugo, Richard Orango, Vitalis Pastakia, Sonak Horowitz, Carol Hogan, Joseph W Vedanthan, Rajesh |
author_sort | Gala, Pooja |
collection | PubMed |
description | OBJECTIVES: Poor medication adherence in low-income and middle-income countries is a major cause of suboptimal hypertension and diabetes control. We aimed to identify key factors associated with medication adherence in western Kenya, with a focus on cost-related and economic wealth factors. SETTING: We conducted a cross-sectional analysis of baseline data of participants enrolled in the Bridging Income Generation with Group Integrated Care study in western Kenya. PARTICIPANTS: All participants were ≥35 years old with either diabetes or hypertension who had been prescribed medications in the past 3 months. PRIMARY AND SECONDARY OUTCOME MEASURES: Baseline data included sociodemographic characteristics, wealth and economic status and medication adherence information. Predictors of medication adherence were separated into the five WHO dimensions of medication adherence: condition-related factors (comorbidities), patient-related factors (psychological factors, alcohol use), therapy-related factors (number of prescription medications), economic-related factors (monthly income, cost of transportation, monthly cost of medications) and health system-related factors (health insurance, time to travel to the health facility). A multivariable analysis, controlling for age and sex, was conducted to determine drivers of suboptimal medication adherence in each overarching category. RESULTS: The analysis included 1496 participants (73.7% women) with a mean age of 60 years (range 35–97). The majority of participants had hypertension (69.2%), 8.8% had diabetes and 22.1% had both hypertension and diabetes. Suboptimal medication adherence was reported by 71.2% of participants. Economic factors were associated with medication adherence. In multivariable analysis that investigated specific subtypes of costs, transportation costs were found to be associated with worse medication adherence. In contrast, we found no evidence of association between monthly medication costs and medication adherence. CONCLUSION: Suboptimal medication adherence is highly prevalent in Kenya, and primary-associated factors include costs, particularly indirect costs of transportation. Addressing all economic factors associated with medication adherence will be important to improve outcomes for non-communicable diseases. TRIAL REGISTRATION NUMBER: NCT02501746. |
format | Online Article Text |
id | pubmed-10481848 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-104818482023-09-07 Cross-sectional analysis of factors associated with medication adherence in western Kenya Gala, Pooja Kamano, Jemima H Vazquez Sanchez, Manuel Mugo, Richard Orango, Vitalis Pastakia, Sonak Horowitz, Carol Hogan, Joseph W Vedanthan, Rajesh BMJ Open Cardiovascular Medicine OBJECTIVES: Poor medication adherence in low-income and middle-income countries is a major cause of suboptimal hypertension and diabetes control. We aimed to identify key factors associated with medication adherence in western Kenya, with a focus on cost-related and economic wealth factors. SETTING: We conducted a cross-sectional analysis of baseline data of participants enrolled in the Bridging Income Generation with Group Integrated Care study in western Kenya. PARTICIPANTS: All participants were ≥35 years old with either diabetes or hypertension who had been prescribed medications in the past 3 months. PRIMARY AND SECONDARY OUTCOME MEASURES: Baseline data included sociodemographic characteristics, wealth and economic status and medication adherence information. Predictors of medication adherence were separated into the five WHO dimensions of medication adherence: condition-related factors (comorbidities), patient-related factors (psychological factors, alcohol use), therapy-related factors (number of prescription medications), economic-related factors (monthly income, cost of transportation, monthly cost of medications) and health system-related factors (health insurance, time to travel to the health facility). A multivariable analysis, controlling for age and sex, was conducted to determine drivers of suboptimal medication adherence in each overarching category. RESULTS: The analysis included 1496 participants (73.7% women) with a mean age of 60 years (range 35–97). The majority of participants had hypertension (69.2%), 8.8% had diabetes and 22.1% had both hypertension and diabetes. Suboptimal medication adherence was reported by 71.2% of participants. Economic factors were associated with medication adherence. In multivariable analysis that investigated specific subtypes of costs, transportation costs were found to be associated with worse medication adherence. In contrast, we found no evidence of association between monthly medication costs and medication adherence. CONCLUSION: Suboptimal medication adherence is highly prevalent in Kenya, and primary-associated factors include costs, particularly indirect costs of transportation. Addressing all economic factors associated with medication adherence will be important to improve outcomes for non-communicable diseases. TRIAL REGISTRATION NUMBER: NCT02501746. BMJ Publishing Group 2023-09-05 /pmc/articles/PMC10481848/ /pubmed/37669842 http://dx.doi.org/10.1136/bmjopen-2023-072358 Text en © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Cardiovascular Medicine Gala, Pooja Kamano, Jemima H Vazquez Sanchez, Manuel Mugo, Richard Orango, Vitalis Pastakia, Sonak Horowitz, Carol Hogan, Joseph W Vedanthan, Rajesh Cross-sectional analysis of factors associated with medication adherence in western Kenya |
title | Cross-sectional analysis of factors associated with medication adherence in western Kenya |
title_full | Cross-sectional analysis of factors associated with medication adherence in western Kenya |
title_fullStr | Cross-sectional analysis of factors associated with medication adherence in western Kenya |
title_full_unstemmed | Cross-sectional analysis of factors associated with medication adherence in western Kenya |
title_short | Cross-sectional analysis of factors associated with medication adherence in western Kenya |
title_sort | cross-sectional analysis of factors associated with medication adherence in western kenya |
topic | Cardiovascular Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10481848/ https://www.ncbi.nlm.nih.gov/pubmed/37669842 http://dx.doi.org/10.1136/bmjopen-2023-072358 |
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