Gender-specific aspects of socialisation and risk of cardiovascular disease among community-dwelling older adults: a prospective cohort study using machine learning algorithms and a conventional method

Achamyeleh Birhanu Teshale,Htet Lin Htun,Alice J Owen,Joanne Ryan,Jr Baker,Mor Vered,Christopher M Reid,Christopher M Reid,Robyn L Woods,Michael Berk,Michael Berk,Andrew Tonkin,Johannes T Neumann,Johannes T Neumann,Johannes T Neumann,Monique F Kilkenny,Monique F Kilkenny,Aung Zaw Zaw Phyo,Mark R Nelson,Nigel Stocks,Carlene Britt,Rosanne Freak-Poli,Rosanne Freak-Poli

doi:10.1136/jech-2023-221860

Gender-specific aspects of socialisation and risk of cardiovascular disease among community-dwelling older adults: a prospective cohort study using machine learning algorithms and a conventional method

Achamyeleh Birhanu Teshale, Htet Lin Htun + Show 21 more

https://doi.org/10.1136/jech-2023-221860

Copy DOI

Journal: Journal of Epidemiology and Community Health	Publication Date: Nov 11, 2024
Citations: 2

#Machine Learning Models #ASPirin In Reducing Events In The Elderly + Show 8 more

Abstract
Full-Text
Similar Papers

Abstract

BackgroundGender influences cardiovascular disease (CVD) through norms, social relations, roles and behaviours. This study identified gender-specific aspects of socialisation associated with CVD.MethodsA longitudinal study was conducted, involving 9936 (5,231 women...

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Similar Papers

Paper Title

Journal

Date

Author

View more papers

More From: Journal of Epidemiology and Community Health

Paper Title

Journal

Date

Author

View more papers

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.