A qualitative study of facilitators and barriers to cardiovascular risk factor control in a semiurban population in India

Cardiovascular (CV) risk factors like diabetes and hypertension are poorly controlled in both rural and urban India. This study was designed to identify the reasons for suboptimal control in a semiurban population in India. A total of 70 participants from the Study to Expand Heart Associated Treatme...

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Detalles Bibliográficos
Autores principales: Satish, Priyanka, Khetan, Aditya, Barbhaya, Dweep, Agarwal, Manyoo, Madan Mohan, Sri Krishna, Josephson, Richard, Webel, Allison R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6924214/
https://www.ncbi.nlm.nih.gov/pubmed/31879612
http://dx.doi.org/10.4103/jfmpc.jfmpc_492_19
Descripción
Sumario:Cardiovascular (CV) risk factors like diabetes and hypertension are poorly controlled in both rural and urban India. This study was designed to identify the reasons for suboptimal control in a semiurban population in India. A total of 70 participants from the Study to Expand Heart Associated Treatments (SEHAT) trial, conducted in West Bengal, India. We qualitatively examined perspectives regarding CV risk factor control using focus group discussions based on the theory of reasoned action. Qualitative content analysis was used to analyze prevailing themes. Participants demonstrated a generalized knowledge of healthy lifestyle practices but lacked insight into disease-specific prevention methods. We further noticed significant gaps in the translation of existing knowledge into behavior. While personal and systemic barriers exist, factors like high patient motivation and a deep sense of trust in providers can potentially be harnessed to improve risk factor control in the community. We identified key facilitators and barriers to CV risk factor control in the community using a knowledge attitude behavior approach. Our findings provide direction for the development of community-based CV risk reduction models.