|Year : 2018 | Volume
| Issue : 1 | Page : 11-16
Determinants of health-related quality of life in stroke survivors in Kano, Northwest Nigeria
Salisu Aliyu1, Aliyu Ibrahim2, Hadiza Saidu3, Lukman F Owolabi2
1 Department of Medicine, General Hospital Katsina, Katsina, Nigeria
2 Department of Medicine, Aminu Kano Teaching Hospital and Bayero University Kano, Kano, Nigeria
3 Department of Medicine, Bayero University Kano, Kano, Nigeria
|Date of Web Publication||29-May-2018|
Dr. Aliyu Ibrahim
Neurology Unit, Department of Medicine, Aminu Kano Teaching Hospital, Bayero University Kano, No. 1 Zaria Road, PMB 3452 Kano
Source of Support: None, Conflict of Interest: None
Background: The long-term consequences of stroke, particularly among the young and middle-aged population in sub-Saharan Africa, constitute a major challenge to the labor work force in resource-limited settings. Previous studies have focused mainly on mortality, recurrence, and functional recovery but less on the quality of life of these patients. We sought to assess the determinants of the health-related quality of life (HRQoL) of stroke survivors in Kano, Northwestern Nigeria.
Material and Methods: A prospective case–control study conducted at Aminu Kano Teaching Hospital, Nigeria over a period of 18 months where 310 (155 patients with stroke and 155 sex- and age-matched healthy controls) participants were assessed using the health-related quality of life in stroke patient-40 (HRQoLISP-40) questionnaire. Multiple logistic regression was used to identify the independent predictors of global HRQoL after controlling for other covariates.
Results: The overall mean global HRQoL scores among the patients with stroke and the controls were 66.1 vs. 86.1, respectively, with a mean difference of −20.0. There mean difference in the physical and spiritual spheres were −28.1 vs. −9.1, respectively. Determinants of the poor quality of life in the stroke survivors were aphasia, lesion location, and poststroke depression.
Conclusion: The HRQoL among the stroke survivors was poor, which demonstrates that the determinants if effectively subjected to evidenced-based therapeutic interventions may lead to improvement in their overall functional recovery and societal reintegration.
Keywords: independent predictors, physical sphere, spiritual sphere
|How to cite this article:|
Aliyu S, Ibrahim A, Saidu H, Owolabi LF. Determinants of health-related quality of life in stroke survivors in Kano, Northwest Nigeria. J Med Trop 2018;20:11-6
|How to cite this URL:|
Aliyu S, Ibrahim A, Saidu H, Owolabi LF. Determinants of health-related quality of life in stroke survivors in Kano, Northwest Nigeria. J Med Trop [serial online] 2018 [cited 2019 Oct 21];20:11-6. Available from: http://www.jmedtropics.org/text.asp?2018/20/1/11/233421
| Introduction|| |
Stroke is a major global health concern and a leading cause of mortality and disability, which may have negative impact on the overall health-related quality of life (HRQoL) of its survivors., The recent increase in the incidence of stroke in low- to middle-income countries, especially in the younger age group, is driven by increasing population size, high human immunodeficiency virus (HIV) prevalence, and stroke risk factors such as hypertension, tobacco use, unhealthy dietary habit, physical inactivity, and obesity.,
Stroke in the young has a disproportionately high economic impact when compared with stroke in the older population, leaving its victims disabled during their most productive years., Sub-Saharan Africa is currently the region with the highest frequency of stroke survivors with stroke-related disabilities. However, previous studies laid emphasis on the recovery of function, recurrence, and mortality but not on the quality of life of stroke surviors., The lack of accessible and affordable thrombolytic therapy may contribute indirectly to the substantial socioeconomic burden, putting enormous strain on the inadequate rehabilitative facilities in our resources limited setting., Research on the dynamics involved in neural injury and repair interacts especially with the patients’ ecosocial environment in predicting functional recovery after stroke.,
The HRQoL-40 composite tool, which was developed and validated locally, can be used to assess and compare the physical and spiritual spheres comprehensively. It also gives an insight into the internal adaptations, coping dynamics, as well as disability-disparity phenomenon in stroke survivors. Furthermore, it predicts both the global and domain-specific factors that can alter the perceived general health, irrespective of the level of activities of daily living (ADL). We undertook this study to determine the HRQoL in stroke survivors in Kano, which is a resource challenged settings in Northwestern Nigeria.
| Materials and methods|| |
A case–control study was 155 participants with stroke and an equal number of sex- and age-matched healthy controls were compared using health-related quality of life in stroke patient-40 (HRQoLISP-40) questionnaire over a period of 18 months (July 1, 2014 to December 31, 2015). Participants in the study group who satisfied the inclusion criteria were recruited by the investigators until the required sample size was obtained (i.e., using systematic random sampling technique). Institutional approval was obtained from the Hospital Research and Ethics Committee before the study was commenced.
The inclusion criteria were the adult patients who suffered a stroke for at least 1 month before recruitment, who have consented to the study personally or by a reliable proxy (usually their caregivers). Excluded from the study were the patients with an ambiguous clinical or radiological diagnosis of stroke, do not have a suitable or reliable proxy (judged reliable if they lived with the patient, had close personal relations with him or her and were sure of the answers to the questions asked in the questionnaire), and those with comorbid medical conditions that could interfere with their QoL (e.g., diabetes, osteoarthritis, chronic kidney disease, decompensated cardiac failure, malignancies, chronic obstructive pulmonary disease, or advanced HIV infections).
The age- and sex-matched apparently healthy controls were from among the members of staff, patients’ relatives, or caregivers who accompanied patients to the clinic.
Instruments used for data collection were the modified mini-mental state examination (mMMSE) questionnaire, modified Rankin scale (mRS), Barthel index (BI) questionnaire, stroke levity score (SLS), and the Hamilton depression scale.
The HRQoLISP-40 has two spheres: the physical sphere and spiritual sphere. The physical sphere consists of four domains (i.e., physical, psychological, cognitive, and ecosocial domains), whereas the spiritual sphere comprises three domains (i.e., soul, spirit, and spiritual interaction domains). The scores in each domain ranges from 0 (worst health) to 100 (best health). The respondents answer all the questions about their QoL honestly giving the nearest most appropriate response while keeping in mind their standards, hopes, pleasures, and concerns in life in the previous 2 weeks.
A mMMSE questionnaire, suitable for application on semiliterate participants and those with no formal education, was used by the researcher to screen for the presence of cognitive impairment. It is a brief 22-point questionnaire. A score of <15 indicated significant cognitive impairment, whereas a score of ≥15 indicated no cognitive impairment.
mRS assesses the degree of disability. It is a reliable stroke disability measure that is good for the overall assessment of disability in the patients with stroke, and it takes approximately 5 min to administer. It is scored between 0 and 6.
BI scale was used to assess the level of independence in performing the ADL among the participants. It is a widely used assessment tool in stroke with excellent validity and reliability, although it has a low sensitivity for the higher level of functioning. It is a 100 point score and usually takes only 15 min to be administered.
The Hamilton depression scale assesses the symptoms of poststroke depression (PSD) among the participants. It is a gold standard scale, frequently used to measure depression in the patients who had stroke with good reliability. It measures mood, anxiety, agitation, and weight loss on the scale of 0 to 4 each. The total score of 0 to 7 is normal, 8 to 10 is mild depression, 11 to 16 is moderate depression, and 17 or more is severe depression.
The SLS was used to determine the stroke severity among our study participants with the test–retest reliability of 0.77 (P < 0.001). It is a measure of stroke severity and outcome that has been validated among the patients with stroke in Nigeria and elsewhere (Chronbach-α of 0.75 in Ibadan) and unlike the National Institute of Health Stroke Scale, it is easier and takes less time to administer (2 min vs. 8 min). SLS = maximum power in the dominant hand + maximum power in the weaker lower limb + mobility score−1 (if aphasia is present). Mobility score has a score of between 1 and 5 (1-bed bound, 2-chair bound, 3-walk with one helper, 4-walk independently with aid, for example, tripod/frame, 5-walk unaided). SLS has a minimum score of 0 and a maximum score of 15. (Mild stroke: 11–15; moderate stroke: 6–10; severe stroke: 0–5.)
The questionnaire was translated to the local language of “Hausa” and administered after pretesting on 16 consenting stroke survivors (∼10% of the sample size) in the neurology outpatient clinic of a selected state tertiary hospital (Murtala Mohammed Specialist Hospital).
| Results|| |
Of the 310 participants enrolled during the study, the mean age ± standard deviation (SD) of the study patients was 58.8 ± 13.3 years, with a male-to-female ratio of 1:1.7, with a median duration of stroke of 24 months. Significant percentage of the study participants (64.5%) did not have any form of formal education. Majority of the study patients with stroke (67.1%) were being supported by their relations and 67.7% of them were satisfied with the level social support they received from these relatives. Ninety-eight (63.2%) patients with stroke had cranial computed tomographic (CT) scan performed and 49.7% had a right hemispheric stroke. The patients differ significantly in terms of stroke location and pathological subtype, because most of the cortical strokes (in 60 cases) were infarctive compared with the subcortical strokes (in 21 cases) that were mainly hemorrhagic (χ2 = 40.345, P < 0.001). Predominant residual motor aphasia was observed in 38.1% of the patients, especially among those with left hemispheric stroke (likelihood ratio = 27.849, P < 0.001). The most common risk factors for stroke were hypertension and dyslipidemia seen in 94.2 and 35.5% of the patients, respectively.
Direct HRQoL rating was performed on 135 (87.1%) of the stroke survivors, whereas the remaining 20 (12.9%) had their HRQoL rated indirectly using their proxies. Stroke survivors were shown to have a lower mean global HRQoL scores compared with that of the controls (mean score of 66.1 vs. 86.1) with a mean difference of −20 [Table 1]. Moreover, the mean difference in HRQoL profile between the participants with stroke and the controls was much greater in physical sphere than in the spiritual sphere (mean difference of −28 vs. −9.1). Consistently the mean difference in HRQoL scores between the cases and the controls was much lower across all the spiritual domains compared with those in physical domains [Figure 1].
|Table 1: Composite HRQoL rating scores of the study participants across the two spheres and seven domains|
Click here to view
|Figure 1: Differences between mean HRQoLISP scores for the patients with stroke and the controls. phy = physical, psyc = psychoemotional, cog = cognitive, ecos = ecosocial, sou = soul, spr = spiritual, spi = spiritual interaction, H-p = HRQoL physical, H-s = HRQoL spiritual|
Click here to view
The mean mRS was 3 with 27.1 and 14.8% of the patients having moderate and severe stroke on SLS, respectively. The moderate (61–90) and severe (21–60) degree of impaired performance of the ADL using BI score was seen in 32.9 and 27.7% of the studied participants, respectively. Predominant motor aphasia (38.1%), PSD (32.2%), and cognitive impairment (21.9%) were seen in the stroke survivors. The results of the binary logistic regression and odds ratio showed that the presence of cortical lesion, aphasia, cognitive impairment, and PSD were the combined predictors of poor global HRQoL among the stroke survivors in this study [Table 2]. Independent predictors of poor global HRQoL in our study after multivariate logistic regressions were aphasia, lesion location, and PSD [Table 3].
|Table 2: Sociodemographic and clinicoanatomic variables associated with of global HRQoL|
Click here to view
| Discussion|| |
Our study revealed an overall poor quality of life scores (below the average global HRQoL, −1 SD) in stroke survivors in Kano, Northwestern Nigeria when compared with the age- and sex-matched controls. This finding is comparable to earlier reports from Nigeria, and parts of Europe,, but differs from the findings reported from New Zealand wherein HRQoL in their stroke survivors was good. This difference may be explained by the assessment of stroke cohorts at 6 years poststroke and the use of a different quality of life assessment tool (generic SF-36 questionnaire) in their study. The tool used in the New Zealand study is associated with a high ceiling and floor effects and may not be sensitive or specific enough to detect various QoL grades over time. However, some studies did not reveal any difference in HRQoL between the patients with stroke and general normative population, possibly because of the use of measurement tools that are not specifically designed for the patients with stroke. When considered together, the above findings may have implications for evidence-based rehabilitative and health resource planning in stroke management. Additionally, the documented pivotal role of spiritual dimension in the care of chronic disorders implied the need for the development of therapeutic strategies aimed at exploiting this sphere for better HRQoL outcomes in stroke survivors.
Although, several clinicoanatomic and sociodemographic variables have reported inconsistent effect on QoL in stroke survivors, our study showed that lesion location (especially cortical), aphasia, cognitive impairment, and PSD predicted poor global HRQoL. However, aphasia, PSD, and lesion location remained the independent determinants of poor HRQoL in stroke survivors on multivariate logistic regression, similar to the findings obtained elsewhere in Nigeria and Germany with the addition of mRS and advancing age as independent determinants of global HRQoL, respectively. The above observation was similar to the findings from Asia where large frontocortical lesions and depressive symptoms were also shown to be the independent predictors of low QoL in stroke survivors. It is not clear by what mechanism these particular stroke lesions lead to a lowering of QoL in stroke survivors; however, these locations represent a major part of frontostriatal circuits, which are closely tied to affective and cognitive processes. Vascular lesion in this location results in the impairment of affection, attention, cognition, and pleasure perception, all of which determine the overall subjective well-being and sensations of the patients with stroke. The impairment of this frontostriatal circuit has also been implicated in resistant depression and PSD to further buttress the finding of our study. The report from New Zealand, however, found an inconclusive relationship between poor QoL and aphasia. This could probably be explained by the exclusion of patients with severe cognitive and communication difficulties, for the fear of providing unreliable results. However, this category forms a large percentage of stroke survivors that consume a greater part of the available resources and could be a major challenge to the limited health budget. Second, the inclusion of acute stroke survivors in Sokoto might have contributed to the significant effect on the overall QoL indirectly making mRS an independent predictor, since time factor affects functional recovery in stroke.
Gender did not predict the poor quality of life in all domains of the physical and spiritual sphere in our study, similar to earlier reports, but this contradicts observations that reported female gender as an independent predictor of good physical functioning or female stroke survivor significantly correlating with poor QoL scores in the physical domain in studies that utilized the Nottingham health profile scale-NHP (a validated QoL measure in Turkey) and SF-36 scale, respectively.,
The limitations of our study included the use of proxies in aphasic stroke survivors, which may lower the rating of QoL as observed in some previous stroke studies. The drawbacks of the BI score for grading functional recovery included stair climbing, which was alternatively assessed with ability to walk up on an incline surface, because most patients did not live in storey buildings. Additionally, the grading did not include the analysis of speech problems, which may allow patient to score maximum points while remaining totally aphasic. Within the limit of these weaknesses, our study is the first of its kind in Kano to use a locally validated multicultural tool to assess the impact of the determinants on HRQoL in stroke survivors, serving as a template for future research in telemedicine.
| Conclusion|| |
The global HRQoL among the stroke survivors was generally low, with lesion location (especially cortical), aphasia, and PSD as the determinants of poor global HRQoL, which was in agreement with previous published data from Nigeria. This study emphasizes the need for physicians to assess for the presence of determinants of poor QoL, which if effectively subjected to evidenced-based therapeutic interventions may lead to the improvement in functional recovery and faster societal reintegration.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Connor MD, Walker R, Modi G, Warlow CP. Burden of stroke in black populations in sub-Saharan Africa. Lancet Neurol 2007;6:269-78.
Owolabi LF, Nagoda M. Factors associated with death and predictors of one month mortality from stroke in Kano, Northwestern Nigeria. J Neurol Rural Pract 2013;4:56-60.
Walker RW, Rolfe M, Kelly PJ, George MO, James OF. Mortality and recovery after stroke in the Gambia. Stroke 2003; 34:1604-9.
Lopez AD, Mathers CD, Ezzati M, Murray CJ. Global and regional burden of diseases and risk factors: Systematic analysis of population health data. Lancet 2006;367:1747-57.
Owolabi LF, Ibrahim A. Stroke in young adults: A prospective study from Northwestern Nigeria. ISRN Neurol 2012;10:1-5.
Smajlović D. Strokes in young adults: Epidemiology and prevention. Vasc Health Risk Manag 2015;11:157-64.
Addington HJ, Kalra L. Who should measure quality of life? BMJ 2001;322:1417-20.
Alkali NH, Bwala SA, Akana AO, Osiogbu OO, Alabi P, Ayeni OA. Stroke risk factors, subtypes and 30 day case fatality in Abuja, Nigeria. Niger J Med 2013;54:129-35.
Connor MD, Thorgood M, Casserly B, Dobson C, Warlow CP, SASPI Project Team. Prevalence of stroke survivors in rural South Africa: Results from Southern Africa stroke prevention initiative (SASPI) Agincourt field site. Stroke 2004;35:627-32.
Bravata DM, Wells CK, Bran LM, Kernon WW, Lag J, Concato J et al.
Racial disparities in stroke risk factors. The impact of socioeconomic status. Stroke 2005;36:1507-11.
Huggues D. Brain plasticity: From pathophysiological mechanisms to therapeutic application. J Clin Neurosci 2009;13:885-7.
Young JA, Tolentino M. Neuroplasticity and its application to rehabilitation. Am J Ther 2011;18:70-80.
Owolabi MO. Psychometric properties of the HRQOLISP-40: A novel, shortened multiculturally valid wholistic stroke measure. J Neurorehab Neural Repair 2010;24:814-25.
Owolabi MO, Ogunniyi A. Profile of health-related quality of life in Nigerian stroke survivors. Eur J Neurol 2009;16:54-62.
Imam I, Ogunniyi A. The value of the mini mental state examination in Nigerian epileptics. Trop Doct 2005;35:108-9.
Bruno A, Akinwuntan AE, Lin C, Close B, Davis K, Baute V et al.
Simplified modified Rankin scale questionnaire reproducibility over the telephone and validation with quality of life. Stroke 2011;42:2276-9.
Lee YC, Chen SS, Koh CL, Hsueh IP, Yao KP, Hsieh CL. Development of two Barthel index-based supplementary scales for patients with stroke. PLoS One 2014;9:1-8.
Ekeh BC, Ogunniyi AO, Isamade EI, Ekrikpo UE. Stroke recovery and its predictors in a Nigerian Teaching Hospital. J Clin Appl Neurosci 2015;1:17-22.
Owolabi MO, Platz T. Proposing the stroke levity scale: A valid, reliable, simple, and time-saving measure of stroke severity. EJNS 2008;15:627-33.
Abubakar SA, Isezuo SA. Health related quality of life of stroke survivors: Experience of a stroke unit. Int J Biomed Sci 2012;8:183-7.
Gokkaya NK, Aras MD, Cakci A. Health related quality of life of Turkish stroke survivors. Int J Rehab Res 2005;28:229-35.
Hackett MA, Maree L, Duncan BA. Health related quality of life among long term survivors of stroke: Result from the Auckland Stroke Study, 1991–1992. Stroke 2000;31:440-7.
Sturm WJ, Helen MD, Thrift AG, Macdonnell RA. Quality of life after stroke: The North East Melbourne Stroke Incidence Study. Stroke 2004;35:715-20.
Patel MD, McKevitt C, Lawrence E, Rudd AG, Wolfe CD. Clinical determinants of long-term quality of life after stroke. Age Ageing 2007;36:316-22.
Moon Y, Se-Joo K, Hyeon-Chul K, Moo-Ho W, Do-Hoon K. Correlate of quality of life after stroke. J Neurol Sci 2004;224:37-41.
Oladiji JO, Akinbo SR, Aina OF, Aiyejesunle CB. Risk factors for post stroke depression among stroke survivors in Lagos. Afr J Psychiatry 2009;12:47-51.
Gray LJ, Sprigg N, Bath PM, Boysen G, De Deyn PP, Leys D et al.
Sex differences in the quality of life in stroke survivors: Data from the ‘Tinzaparin in Acute Ischemic Stroke Trial’. Stroke 2007;38:2960-4.
Pickard AS, Johnson JA, Feeny DH, Shuaib A, Carriere KC, Nasser AM. Agreement between patient and proxy assessment of health-related quality of life after stroke using the EQ-5D and health utilities index. Stroke 2004;35:607-12.
[Table 1], [Table 2], [Table 3]