Fatigue as a long-term risk factor for limitations in instrumental activities of daily living and/or mobility performance in older adults after 10 years

Abstract

ObjectivesDecline in the performance of instrumental activities of daily living (IADL) and mobility may be preceded by symptoms the patient experiences, such as fatigue. The aim of this study is to investigate whether self-reported non-task-specific fatigue is a long-term risk factor for IADL-limitations and/or mobility performance in older adults after 10 years.MethodsA prospective study from two previously conducted cross-sectional studies with 10-year follow-up was conducted among 285 males and 249 females aged 40–79 years at baseline. Fatigue was measured by asking “Did you feel tired within the past 4 weeks?” (males) and “Do you feel tired?” (females). Self-reported IADLs were assessed at baseline and follow-up. Mobility was assessed by the 6-minute walk test. Gender-specific associations between fatigue and IADL-limitations and mobility were estimated by multivariable logistic and linear regression models.ResultsA total of 18.6% of males and 28.1% of females were fatigued. After adjustment, the odds ratio for fatigued versus non-fatigued males affected by IADL-limitations was 3.3 (P=0.023). In females, the association was weaker and not statistically significant, with odds ratio being 1.7 (P=0.154). Fatigued males walked 39.1 m shorter distance than those non-fatigued (P=0.048). For fatigued females, the distance was 17.5 m shorter compared to those non-fatigued (P=0.479).ConclusionOur data suggest that self-reported fatigue may be a long-term risk factor for IADL-limitations and mobility performance in middle-aged and elderly males but possibly not in females.

Modifiable factors related to life-space mobility in community-dwelling older adults: results from the Canadian Longitudinal Study on Aging

“…Modifiable factors were selected using Webber's conceptual framework of life-space mobility [9] and previous research evidence where factors that demonstrated an association with mobility were identified. Factors were categorized in accordance with Webber's framework, including physical [17,18,23], psychosocial [24,25] and cognitive determinants [26], alongside other factors that were highlighted in previous studies, such as pain [27], fatigue [28], driving status [29], nutrition [30,31], body mass index [32], smoking status [33,34] and vision [35].…”

Fatigue and the prediction of negative health outcomes: A systematic review with meta-analysis

“…In total 9 studies described the relationship between fatigue and mortality (Avlund et al, 1998, Avlund et al, 2003a, Basu et al, 2016, Cole et al, 1999, Hardy and Studenski, 2008, Moreh et al, 2009, Moreh et al, 2010, Prescott et al, 2003, Schultz-Larsen and Avlund, 2007b, 9 articles discussed different diseases (Bergelt et al, 2005, Ekmann et al, 2013, Iversen et al, 2012, Just-Ostergaard et al, 2018, Kornerup et al, 2010, Pedersen et al, 2016, Prescott et al, 2003, Volden et al, 2017, Williams et al, 2010) (of which 3 discussed heart disease), 8 articles looked at physical functioning expressed in physical J o u r n a l P r e -p r o o f activity (Moreh et al, 2010), physical capacity and gait (Simonsick et al, 2016, Simonsick et al, 2018 while others expressed physical functioning on the Mobility Help scale (Avlund et al, 1995, Idland et al, 2013, Avlund et al, 2003b, Avlund et al, 2003a, Schultz-Larsen and Avlund, 2007b. Four articles described the prospective value of fatigue on disability in Activities of Daily Living (ADL's) (Avlund et al, 1995, Avlund et al, 2002b, Moreh et al, 2010, Mueller-Schotte et al, 2016, 3 investigated hospitalization (Avlund et al, 2001a, Rod et al, 2011, Zaslavsky et al, 2014, and the remaining single articles investigated falls (Kamitani et al, 2017), healthcare utilization (Avlund et al, 2001a), self-reported health…”

“…Twelve different studies described the Maastricht Questionnaire within 4 large cohorts as a prognostic factor, to predict several diseases including heart diseases (n=3) (Prescott et al, 2003, Rod et al, 2011, Islamoska et al, 2019, Just-Ostergaard et al, 2018, Kornerup et al, 2010, Pedersen et al, 2016, Volden et al, 2017, Bergelt et al, 2005, Williams et al, 2010. Another approach to evaluate fatigue is the 36-item short-form survey (SF-36) (Hays et al, 1993), the vitality subscale of the SF-36 was 6 times applied in the included studies to predict physical functioning, mortality, ADL disability, hospitalization, falls and pain (Aili et al, 2018, Basu et al, 2016, Kamitani et al, 2017, Mueller-Schotte et al, 2016, Zaslavsky et al, 2017. Avlund et al (2008) derived one question from the 12-Item Short Form Survey (SF-12) (Ware et al, 1996) "How much of the time during the past four weeks did you have a lot of energy?"…”

Impact of Baseline Fatigue on a Physical Activity Intervention to Prevent Mobility Disability

“…Fatigue is a commonly experienced symptom reported by older adults, and individuals with lower levels of PA are more likely to feel fatigued . Higher levels of fatigue also have been associated with lower physical functioning, slower gait speed, poorer mobility, and worse performance in instrumental activities of daily living, with a greater mortality risk …”

“…5,6 Higher levels of fatigue also have been associated with lower physical functioning, slower gait speed, poorer mobility, and worse performance in instrumental activities of daily living, with a greater mortality risk. [7][8][9][10][11][12][13] Because higher levels of fatigue are associated with less PA, 10,14,15 this relationship may contribute to the pathway feeding functional decline, disablement, and mortality. 10 Some evidence indicated that those with higher levels of fatigue may benefit more from PA interventions.…”