Effects of lifestyle risk behaviour clustering on cardiovascular disease among UK adults: latent class analysis with distal outcomes

Islam, Sheikh Mohammed Shariful; Maddison, Ralph

doi:10.21203/rs.3.rs-1986313/v1

Cited by 2 publications

References 41 publications

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Daily Activity Lifelogs of People With Heart Failure: Observational Study

Tegegne,

Tran,

Nourse

et al. 2024

JMIR Form Res

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Background Globally, heart failure (HF) affects more than 64 million people, and attempts to reduce its social and economic burden are a public health priority. Interventions to support people with HF to self-manage have been shown to reduce hospitalizations, improve quality of life, and reduce mortality rates. Understanding how people self-manage is imperative to improve future interventions; however, most approaches to date, have used self-report methods to achieve this. Wearable cameras provide a unique tool to understand the lived experiences of people with HF and the daily activities they undertake, which could lead to more effective interventions. However, their potential for understanding chronic conditions such as HF is unclear. Objective This study aimed to determine the potential utility of wearable cameras to better understand the activities of daily living in people living with HF. Methods The “Seeing is Believing (SIB)” study involved 30 patients with HF who wore wearable cameras for a maximum of 30 days. We used the E-Myscéal web-based lifelog retrieval system to process and analyze the wearable camera image data set. Search terms for 7 daily activities (physical activity, gardening, shopping, screen time, drinking, eating, and medication intake) were developed and used for image retrieval. Sensitivity analysis was conducted to compare the number of images retrieved using different search terms. Temporal patterns in daily activities were examined, and differences before and after hospitalization were assessed. Results E-Myscéal exhibited sensitivity to specific search terms, leading to significant variations in the number of images retrieved for each activity. The highest number of images returned were related to eating and drinking, with fewer images for physical activity, screen time, and taking medication. The majority of captured activities occurred before midday. Notably, temporal differences in daily activity patterns were observed for participants hospitalized during this study. The number of medication images increased after hospital discharge, while screen time images decreased. Conclusions Wearable cameras offer valuable insights into daily activities and self-management in people living with HF. E-Myscéal efficiently retrieves relevant images, but search term sensitivity underscores the need for careful selection.

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Daily Activity Lifelogs of People With Heart Failure: Observational Study

Tegegne,

Tran,

Nourse

et al. 2024

JMIR Form Res

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View full text Add to dashboard Cite

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Daily Activity Lifelogs of People With Heart Failure: Observational Study (Preprint)

Tran¹,

Nourse²,

Gurrin³

et al. 2023

Preprint

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BACKGROUND Globally, heart failure (HF) affects more than 64 million people and attempts to reduce its social and economic burden is a public health priority. Interventions to support people with HF to self-manage have been shown to reduce hospitalisations, improve quality of life, and reduce mortality rates. Understanding how people self-manage is imperative to improve future interventions; however, most approaches to date, have used self-report methods to achieve this. Wearable cameras provide a unique tool to understand the lived experiences of people with HF and the daily activities they undertake, which could lead to more effective interventions. However, their potential for understanding chronic conditions such as HF is unclear. OBJECTIVE The aim of this study was to determine the potential utility of wearable cameras to better understand activities of daily living in people living with HF. METHODS This study analysed wearable camera image data obtained from people living with HF. Images were processed using the E-Myscéal system with customized search terms for seven activities of daily living (physical activity, gardening, shopping, screen time, drinking, eating, and taking medication). The utility of the system for capturing specific activities was evaluated using sensitivity analysis. Daily activity image data were analysed using descriptive statistics. Differences in recorded activities were also captured for 10 participants that were readmitted to hospital for HF. RESULTS The E-Myscéal system demonstrated heightened sensitivity towards specific search terms. Overall, a higher number of images were recorded for eating and drinking, while the number of images for physical activity, screen time and taking medication was lower. More activities were recorded before midday compared with afternoons. Changes in the participants' daily activities were also observed before and after their hospitalization. CONCLUSIONS Wearable cameras can capture valuable data on daily activities of people living with HF to develop personalized interventions. A flexible interrogation system is crucial for efficient analysis of the huge volume of data produced by lifelogging devices.

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Effects of lifestyle risk behaviour clustering on cardiovascular disease among UK adults: latent class analysis with distal outcomes

Cited by 2 publications

References 41 publications

Daily Activity Lifelogs of People With Heart Failure: Observational Study

Daily Activity Lifelogs of People With Heart Failure: Observational Study

Daily Activity Lifelogs of People With Heart Failure: Observational Study (Preprint)

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