1. Background
Stroke is a major cause of mortality and debility in Nigeria (1, 2) as it is globally. The debility from stroke often results from several consequences of the disease. One major, but often-neglected stroke sequela that has a profoundly distressing effect is poststroke fatigue (PSF) (3, 4).
PSF can be described as a feeling of exhaustion, weariness, lack of energy, and aversion of effort after stroke (5, 6). It is known to adversely affect functional ability (3), quality of life, and well being of stroke survivors (3, 7). With prevalence rates as high as 75% (8), PSF remains a major source of concern to stroke survivors and their caregivers. Additionally, the stroke survivor’s ability to actively participate in rehabilitation strategies including physical therapy may be markedly restricted by PSF. Going by these debilitating effects of PSF, gaining insight into the mechanism of PSF, is of utmost importance and information on features that may represent its risk factors is therefore very crucial. For instance, successful and effective management of PSF would be dependent on addressing its risk factors. Furthermore, information on the determinants of PSF would assist in identifying stroke patients at risk of PSF and consequently facilitate the provision of early preventive and management strategies.
Several studies have been conducted in various regions of the world on the determinants or risk factors of PSF (4). While findings are largely conflicting and apparently inconclusive (9), some studies have shown significant associations between PSF and demographic factors such as female gender (10-12) and older age (10, 11, 13). Similarly, there is some evidence that clinical factors such as functional ability and pre-stroke fatigue influence PSF (3, 4, 14, 15).
While an overwhelming majority of data on determinants of PSF is from Asian and developed Western countries (3, 10-15), there is a dearth of information on the subject in developing countries including African countries such as Nigeria. There is however a need for country-specific data especially as there are reports on association between race/ethnicity and fatigue (16, 17). To bridge the existing gap in the literature, this study therefore examined determinants of PSF among stroke survivors undergoing physiotherapy on outpatient basis in Nigeria. The associations between PSF and distinctive personal factors, namely socio-demographic and clinical characteristics of stroke survivors, were examined.
2. Methods
Study design: A hospital-based cross-sectional study was conducted.
Study site: Physiotherapy facilities at 2 government hospitals in Northeast Nigeria.
Participants: Participants included community dwelling stroke survivors who were recipients of physiotherapy at the time of the study. Those aged 18 years and above, who were able to communicate verbally (in order to respond to the interview questions), and who expressed their willingness to participate in the study were recruited. Those with conditions that often result in fatigue such as cancers and arthritis were excluded from the study.
Instruments: Researcher-designed data forms were utilized to record socio-demographic (gender, age, marital status, education level, prestroke occupation, and poststroke employment status) and clinical (type and side of stroke, poststroke duration, and nature of stroke [first-ever/recurrent]) data obtained from the participants.
Fatigue severity scale (FSS): the 9-item FSS (18) was used to assess PSF. Each item evaluates the effect of fatigue on performance of daily activities using a 7-point Likert scale of 1 (strongly disagree) to 7 (strongly agree). The overall FSS score ranges from 1 to 7 and is obtained from the arithmetic mean of the summation of scores from each of the 9 items. Higher overall score depicts higher level of fatigue. The FSS has good reliability (19) and appears to be the tool most commonly used to assess PSF in stroke studies (9).
Modified rankin scale (mRS): the mRS is a global disability assessment tool (20), which was used to assess functional ability of the study participants. It assesses disability on a 6-point ordinal scale, which ranges from 0 (no disability) to 5 (severe disability). The mRS is reliable and valid and one of the most common scales used in stroke studies (20, 21).
2.1. Procedure
Ethical approval was obtained from the institutional ethical committee of one of the participating hospitals. Consenting stroke survivors were consecutively recruited into the study written informed consent was obtained from each participant. The study instruments were administered through face-to-face interviews by the second author. The study was conducted in the year 2013.
2.2. Statistical Analyses
Descriptive statistics of frequencies, percentages, range, mean, and standard deviation were used to summarize the data obtained. Multiple regression analysis (‘enter’ method) was used to identify the independent determinants of PSF among the socio-demographic and clinical data obtained from the participants. The dependent variable was PSF (represented by the overall score on the FSS) while the independent variables were gender, age, marital status, education level, poststroke employment status (returned to work or not), type, side and nature (first/recurrent) of stroke, poststroke duration, and functional ability. Level of statistical significance was set at alpha equals 0.05.
3. Results
One hundred stroke survivors participated in the study. Males (66%), the married (83%), and survivors of ischemic stroke (70%) were the majority. Mean age and mean post stroke duration was 55.3 ± 13.8 years and 12.6 ± 19.3 months, respectively. Details of the socio-demographic and clinical characteristics of the participants are presented in Table 1.
Table 1.Socio-Demographic and Clinical Characteristics of Participants (N = 100)a
| Characteristic | Value |
|---|---|
| Age, y | |
| Mean ± SD | 55.3 ± 13.9 |
| Range | 18 - 85 |
| Poststroke duration, mo | |
| Mean ± SD | 12.6 ± 19.3 |
| Range | 0.5 - 144 |
| Gender | |
| Male | 66 (66) |
| Female | 34 (34) |
| Marital status | |
| Married | 83(83) |
| Single | 7 (7) |
| Widowed | 10 (10) |
| Educational level | |
| None | 8 (8) |
| Primary | 9 (9) |
| Secondary | 19 (19) |
| Tertiary | 35 (35) |
| Qur’anic | 29 (29) |
| Side of stroke | |
| Right | 49 (49) |
| Left | 51 (51) |
| Type of stroke | |
| Ischemic | 70 (70) |
| Hemorrhagic | 30 (30) |
| Occupation status | |
| Civil servant | 18 (18) |
| Housewife | 18 (18) |
| Retiree | 22 (22) |
| Student | 2 (2) |
| Self employed | 38 (38) |
| Unemployed | 2 (2) |
| Nature of Stroke | |
| First-ever | 68 (68) |
| Recurrent | 32 (32) |
aData are presented as mean ± SD or No (%).
3.1. Determinants of PSF
The result of the multiple regression analysis that R2 = 0.33 indicating that the regression model that included all the socio-demographic and clinical data was responsible for 33% of the variance in PSF. However, only functional ability emerged as a significant determinant of PSF at P < 0.001 with β = 0.59 (Table 2).
Table 2.Multiple Regression Analysis for Determinants of Poststroke Fatigue
| Independent Variable | β | P Value |
|---|---|---|
| Age | -0.09 | 0.33 |
| Gender | -0.11 | 0.31 |
| Marital status | 0.04 | 0.71 |
| Educational level | 0.07 | 0.44 |
| Employment status | 0.02 | 0.82 |
| Poststroke duration | 0.06 | 0.53 |
| Type of stroke | 0.01 | 0.92 |
| Side of stroke | 0.16 | 0.09 |
| Nature of stroke | -0.06 | 0.48 |
| Functional ability, mRS | 0.58 | 0.00a |
Abbreviation: mRS, modified rankin scale.
aSignificant at P < 0.0001; R2 = 0.33.
4. Discussion
Poststroke fatigue (PSF) is known to result in a number of adverse consequences and negatively impacts on the well-being and quality of life of stroke survivors (3, 7). Understanding the mechanism of PSF, especially as it concerns its risk of factors is therefore of utmost importance. This study explored the determinants of PSF among stroke survivors undergoing outpatient rehabilitation at physiotherapy facilities in Nigeria.
Of the socio-demographic and clinical data obtained from the participants in the study, only level of functional ability was found to be significantly and independently associated with PSF with poor level of function emerging as a determinant of PSF. While many of the previous studies that investigated the determinants of PSF have reported conflicting and inconclusive findings, the impact of level of functional ability (or disability) appears be fairly consistent across studies (4, 15, 17, 22, 23). A recent systematic review of PSF literature showed that 25 studies found a significant association between PSF and functional ability while 15 studies did not (4). While the above mentioned studies were conducted in Western and Asian countries, this present study represents one of the few from Africa. The observed significant impact of functional disability on the occurrence of PSF across studies notwithstanding the location and setting of the studies buttresses the crucial need for evidence-based stroke rehabilitation strategies that are capable of reducing functional disability after stroke. This need is particularly important in low-resource settings like ours where rehabilitation personnel and facilities are grossly inadequate to effectively address post stroke functional disability. Hence, the finding of this study adds further credence to the perennial call for urgent financial, training, and organizational interventions to improve the standard of stroke rehabilitation in Nigeria as these will assist in the successful management of post-stroke functional disability and subsequently combat PSF and its debilitating effects.
In addition to level of functional disability, other clinical factors that have been previously identified as determinants of PSF include pre-stroke fatigue and depression (3, 14, 15). Although no information was obtained regarding these 2 factors in the present study, the fact that they are both potentially amenable to appropriate interventions is especially important given the negative consequences of PSF. It would therefore be necessary for future studies in our settings to evaluate the impact of pre stroke fatigue and depression on post stroke fatigue.
The cross-sectional design of the study constitutes a limitation especi becuse the identification of poor functional ability as the risk factor for PSF using this design does not rule out reverse causality in the relationship between functional ability and PSF. Future studies utilizing prospective and longitudinal designs would therefore be required. The small size of the sample of stroke survivors and the fact that they were recruited from hospital settings may also decrease the external validity of the findings.
3.1. Conclusions
Among factors such as gender, age, marital status, education level, post stroke employment status, type, side and nature of stroke, as well as post stroke duration, only poor functional ability emerged as an independent and significant determinant of PSF among stroke survivors in the study. This important association between functional disability and PSF has implications for effective and proven functional ability-enhancing stroke rehabilitation strategies.
