An individually adjusted approach for communicating epidemiological results on health and lifestyle to patients

If scientific research on modifiable risk factors was more accessible to the general population there is a potential to prevent disease and promote health. Mobile applications can automatically combine individual characteristics and statistical models of health to present scientific information as i...

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Published in:Scientific Reports
Main Authors: Waaler, Per Niklas Benzler, Bongo, Lars Ailo Aslaksen, Rolandsen, Christina, Lorem, Geir Fagerjord
Format: Article in Journal/Newspaper
Language:English
Published: Springer Nature 2024
Subjects:
Online Access:https://hdl.handle.net/10037/34481
https://doi.org/10.1038/s41598-024-53275-x
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author Waaler, Per Niklas Benzler
Bongo, Lars Ailo Aslaksen
Rolandsen, Christina
Lorem, Geir Fagerjord
author_facet Waaler, Per Niklas Benzler
Bongo, Lars Ailo Aslaksen
Rolandsen, Christina
Lorem, Geir Fagerjord
author_sort Waaler, Per Niklas Benzler
collection University of Tromsø: Munin Open Research Archive
container_issue 1
container_title Scientific Reports
container_volume 14
description If scientific research on modifiable risk factors was more accessible to the general population there is a potential to prevent disease and promote health. Mobile applications can automatically combine individual characteristics and statistical models of health to present scientific information as individually tailored visuals, and thus there is untapped potential in incorporating scientific research into apps aimed at promoting healthier lifestyles. As a proof-of-concept, we develop a statistical model of the relationship between Self-rated-health (SRH) and lifestyle-related factors, and a simple app for conveying its effects through a visualisation that sets the individual as the frame of reference. Using data from the 6th (n= 12 981, 53.4% women and 46.6% men) and 7th (n= 21 083, 52.5% women and 47.5% men) iteration of the Tromsø population survey, we fitted a mixed effects linear regression model that models mean SRH as a function of self-reported intensity and frequency of physical activity (PA), BMI, mental health symptoms (HSCL-10), smoking, support from friends, and HbA1c ≥ 6.5%. We adjusted for socioeconomic and demographic factors and comorbidity. We designed a simple proof-of-concept app to register relevant user information, and use the SRH-model to translate the present status of the user into suggestions for lifestyle changes along with predicted health effects. SRH was strongly related to modifiable health factors. The strongest modifiable predictors of SRH were mental health symptoms and PA. The mean adjusted difference in SRH between those with 10-HSCL index = 1.85 (threshold for mental distress) and HSCL-10 = 1 was 0.59 (CI 0.61–0.57). Vigorous physical activity (exercising to exhaustion≥ 4 days/week relative to sedentary) was associated with an increase on the SRH scale of 0.64 (CI 0.56–0.73). Physical activity intensity and frequency interacted positively, with large PA-volume (frequency ⨯ intensity) being particularly predictive of high SRH. Incorporating statistical models of health into ...
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Waaler, Bongo, Rolandsen, Lorem. An individually adjusted approach for communicating epidemiological results on health and lifestyle to patients. Scientific Reports. 2024;14(1):3199
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https://hdl.handle.net/10037/34481
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spelling ftunivtroemsoe:oai:munin.uit.no:10037/34481 2025-04-13T14:27:39+00:00 An individually adjusted approach for communicating epidemiological results on health and lifestyle to patients Waaler, Per Niklas Benzler Bongo, Lars Ailo Aslaksen Rolandsen, Christina Lorem, Geir Fagerjord 2024-02-08 https://hdl.handle.net/10037/34481 https://doi.org/10.1038/s41598-024-53275-x eng eng Springer Nature Scientific Reports Waaler, Bongo, Rolandsen, Lorem. An individually adjusted approach for communicating epidemiological results on health and lifestyle to patients. Scientific Reports. 2024;14(1):3199 FRIDAID 2249594 https://hdl.handle.net/10037/34481 Attribution 4.0 International (CC BY 4.0) openAccess Copyright 2024 The Author(s) https://creativecommons.org/licenses/by/4.0 Journal article Tidsskriftartikkel Peer reviewed publishedVersion 2024 ftunivtroemsoe https://doi.org/10.1038/s41598-024-53275-x 2025-03-14T05:17:56Z If scientific research on modifiable risk factors was more accessible to the general population there is a potential to prevent disease and promote health. Mobile applications can automatically combine individual characteristics and statistical models of health to present scientific information as individually tailored visuals, and thus there is untapped potential in incorporating scientific research into apps aimed at promoting healthier lifestyles. As a proof-of-concept, we develop a statistical model of the relationship between Self-rated-health (SRH) and lifestyle-related factors, and a simple app for conveying its effects through a visualisation that sets the individual as the frame of reference. Using data from the 6th (n= 12 981, 53.4% women and 46.6% men) and 7th (n= 21 083, 52.5% women and 47.5% men) iteration of the Tromsø population survey, we fitted a mixed effects linear regression model that models mean SRH as a function of self-reported intensity and frequency of physical activity (PA), BMI, mental health symptoms (HSCL-10), smoking, support from friends, and HbA1c ≥ 6.5%. We adjusted for socioeconomic and demographic factors and comorbidity. We designed a simple proof-of-concept app to register relevant user information, and use the SRH-model to translate the present status of the user into suggestions for lifestyle changes along with predicted health effects. SRH was strongly related to modifiable health factors. The strongest modifiable predictors of SRH were mental health symptoms and PA. The mean adjusted difference in SRH between those with 10-HSCL index = 1.85 (threshold for mental distress) and HSCL-10 = 1 was 0.59 (CI 0.61–0.57). Vigorous physical activity (exercising to exhaustion≥ 4 days/week relative to sedentary) was associated with an increase on the SRH scale of 0.64 (CI 0.56–0.73). Physical activity intensity and frequency interacted positively, with large PA-volume (frequency ⨯ intensity) being particularly predictive of high SRH. Incorporating statistical models of health into ... Article in Journal/Newspaper Tromsø University of Tromsø: Munin Open Research Archive Tromsø Scientific Reports 14 1
spellingShingle Waaler, Per Niklas Benzler
Bongo, Lars Ailo Aslaksen
Rolandsen, Christina
Lorem, Geir Fagerjord
An individually adjusted approach for communicating epidemiological results on health and lifestyle to patients
title An individually adjusted approach for communicating epidemiological results on health and lifestyle to patients
title_full An individually adjusted approach for communicating epidemiological results on health and lifestyle to patients
title_fullStr An individually adjusted approach for communicating epidemiological results on health and lifestyle to patients
title_full_unstemmed An individually adjusted approach for communicating epidemiological results on health and lifestyle to patients
title_short An individually adjusted approach for communicating epidemiological results on health and lifestyle to patients
title_sort individually adjusted approach for communicating epidemiological results on health and lifestyle to patients
url https://hdl.handle.net/10037/34481
https://doi.org/10.1038/s41598-024-53275-x