Sofie Holmquist1, Sabina Mattsson1,2, Ingrid Schele1, Peter Nordström3, Anna Nordström4. 1. Department of Psychology, Umeå University, Umeå, Sweden. 2. School of Sport Sciences, UiT The Arctic University of Norway, Tromsø, Norway. 3. Department of Community Medicine and Rehabilitation, Geriatric Medicine, Umeå University, Umeå, Sweden. 4. Department of Public Health and Clinical Medicine, Occupational and Environmental Medicine, Umeå University, Umeå, Sweden.
Abstract
BACKGROUND: The identification of potential high-risk groups for depression is of importance. The purpose of the present study was to identify high-risk profiles for depressive symptoms in older individuals, with a focus on functional performance. METHODS: The population-based Healthy Ageing Initiative included 2,084 community-dwelling individuals (49% women) aged 70. Explorative cluster analysis was used to group participants according to functional performance level, using measures of basic mobility skills, gait variability, and grip strength. Intercluster differences in depressive symptoms (measured by the Geriatric Depression Scale [GDS]-15), physical activity (PA; measured objectively with the ActiGraph GT3X+), and a rich set of covariates were examined. RESULTS: The cluster analysis yielded a seven-cluster solution. One potential high-risk cluster was identified, with overrepresentation of individuals with GDS scores >5 (15.1 vs. 2.7% expected; relative risk = 6.99, P < .001); the prevalence of depressive symptoms was significantly lower in the other clusters (all P < .01). The potential high-risk cluster had significant overrepresentations of obese individuals (39.7 vs. 17.4% expected) and those with type 2 diabetes (24.7 vs. 8.5% expected), and underrepresentation of individuals who fulfilled the World Health Organization's PA recommendations (15.6 vs. 59.1% expected; all P < .01), as well as low levels of functional performance. CONCLUSIONS: The present study provided a potential high-risk profile for depressive symptoms among elderly community-dwelling individuals, which included low levels functional performance combined with low levels of PA. Including PA in medical screening of the elderly may aid in identification of potential high-risk individuals for depressive symptoms.
BACKGROUND: The identification of potential high-risk groups for depression is of importance. The purpose of the present study was to identify high-risk profiles for depressive symptoms in older individuals, with a focus on functional performance. METHODS: The population-based Healthy Ageing Initiative included 2,084 community-dwelling individuals (49% women) aged 70. Explorative cluster analysis was used to group participants according to functional performance level, using measures of basic mobility skills, gait variability, and grip strength. Intercluster differences in depressive symptoms (measured by the Geriatric Depression Scale [GDS]-15), physical activity (PA; measured objectively with the ActiGraph GT3X+), and a rich set of covariates were examined. RESULTS: The cluster analysis yielded a seven-cluster solution. One potential high-risk cluster was identified, with overrepresentation of individuals with GDS scores >5 (15.1 vs. 2.7% expected; relative risk = 6.99, P < .001); the prevalence of depressive symptoms was significantly lower in the other clusters (all P < .01). The potential high-risk cluster had significant overrepresentations of obese individuals (39.7 vs. 17.4% expected) and those with type 2 diabetes (24.7 vs. 8.5% expected), and underrepresentation of individuals who fulfilled the World Health Organization's PA recommendations (15.6 vs. 59.1% expected; all P < .01), as well as low levels of functional performance. CONCLUSIONS: The present study provided a potential high-risk profile for depressive symptoms among elderly community-dwelling individuals, which included low levels functional performance combined with low levels of PA. Including PA in medical screening of the elderly may aid in identification of potential high-risk individuals for depressive symptoms.
Authors: Ewa Zasadzka; Anna Pieczyńska; Tomasz Trzmiel; Paweł Kleka; Mariola Pawlaczyk Journal: Int J Environ Res Public Health Date: 2021-04-30 Impact factor: 3.390
Authors: Åsa von Berens; Roger A Fielding; Thomas Gustafsson; Dylan Kirn; Jonathan Laussen; Margaretha Nydahl; Kieran Reid; Thomas G Travison; Hao Zhu; Tommy Cederholm; Afsaneh Koochek Journal: BMC Geriatr Date: 2018-11-21 Impact factor: 3.921
Authors: Yecheng Yao; Gangqiang Ding; Liaoliao Wang; Ye Jin; Jianwei Lin; Yujia Zhai; Tao Zhang; Fan He; Weigang Fan Journal: Int J Environ Res Public Health Date: 2019-10-24 Impact factor: 3.390