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Self-Reported Fatigue Predicts Incident Stroke in a General Population: EPIC-Norfolk Prospective Population-Based Study.

ABSTRACT: Background and Purpose- Fatigue is a common symptom among stroke survivors and in general practice. However, the clinical significance of fatigue and its relationship to incident stroke is unclear. The aim of this study was to examine the relationship between self-reported fatigue and the incidence of stroke in a general population. Methods- This was a prospective, population-based study. The study population was 15 654 men and women aged 39 to 79 years recruited in 1993 to 1997 and followed till March 2016. Fatigue was assessed at 18 months after baseline using the vitality domain of the Short Form 36 questionnaire. Cox proportional hazard models were constructed to describe the prospective relationship between baseline fatigue and incident stroke adjusting for age, sex, systolic blood pressure, cholesterol, physical activity, smoking status, alcohol consumption, fruit and vegetable consumption, diabetes mellitus, body mass index, vitamin supplement use, education level, Townsend deprivation index, and occupational social class. Incident stroke was ascertained using death certificates and hospital record linkage data. Results- Through 249 248 person-years of follow-up, 1509 incident strokes occurred. Participants who reported the highest level of fatigue (quartile 4) were more likely to be women, to be multimorbid, and to perceive their health as fair or poor. We observed ≈50% relative risk increase in stroke risk (hazard ratio, 1.49 [95% CI, 1.29-1.71]) in those who reported the highest level of fatigue compared with those who reported the lowest level of fatigue (Q4 versus Q1). This relationship remained unaltered regardless of anemia status, the presence or absence of chronic bronchitis, thyroid dysfunction, or depression. Conclusions- Self-report fatigue assessed by the vitality domain of the Short Form 36 questionnaire predicts the risk of future stroke at the general population level. Identifying and addressing stroke risk factors in those who report fatigue in general practice may have substantial benefit at the population level.

SUBMITTER: Barlas G

PROVIDER: S-EPMC7611120 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:While physical activity interventions have been reported to reduce hospital stays, it is not clear if, in the general population, usual physical activity patterns may be associated with subsequent hospital use independently of other lifestyle factors. OBJECTIVE:We examined the relationship between reported usual physical activity and subsequent admissions to hospital and time spent in hospital for 11,228 men and 13,786 women aged 40-79?years in the general population. METHODS:Participants from a British prospective population-based cohort study were followed for 20?years (1999-2019) using record linkage to document hospital usage. Total physical activity was estimated by combining workplace and leisure time activity reported in a baseline lifestyle questionnaire and repeated in a subset at a second time point approximately 12?years later. RESULTS:Compared to those reporting no physical activity, participants who were the most active had a lower likelihood of spending more than 20?days in hospital odds ratio (OR) 0.88 (95% confidence interval (CI) 0.81-0.96) over the next 20?years after multivariable adjustment for age, sex, smoking status, education, social class and body mass index. Participants reporting any activity had a mean of 0.42 fewer hospital days per year between 1999 and 2009 compared to inactive participants, an estimated potential saving to the National Health Service (NHS) of £247 per person per year, or approximately 7% of UK health expenditure. Participants who remained physically active or became active 12?years later had lower risk of subsequent hospital usage than those who remained inactive or became inactive, p-trend <?0.001. CONCLUSION:Usual physical activity in this middle-aged and older population predicts lower future hospitalisations - time spent in hospital and number of admissions independently of behavioural and sociodemographic factors. Small feasible differences in usual physical activity in the general population may potentially have a substantial impact on hospital usage and costs.

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Self-Reported Fatigue Predicts Incident Stroke in a General Population: EPIC-Norfolk Prospective Population-Based Study.

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