Quality of Life and Associated Factors among Adults with Epilepsy in Nigeria

Mosaku, Kolawole Samuel; Fatoye, F O; Komolafe, Morenikeji; Lawal, Musiliu Adejare; Ola, Bolanle

doi:10.2190/r80g-580x-x1h2-6936

Cited by 46 publications

(39 citation statements)

References 37 publications

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“…Eight studies reported no association between employment and HRQoL. Of these, four had sample sizes <115 and, therefore, low statistical power (Loring et al., 2004; Thomas et al., 2005; Meldolesi et al., 2006; Mosaku et al., 2006; Zhao et al., 2008). Other demographic factors (e.g., socioeconomic status, financial income) were evaluated in only a few studies and, therefore, there is insufficient information to comment on their associative status with HRQoL.…”

Section: Resultsmentioning

confidence: 99%

“…Ten others reported no association. Of these, five studies (Loring et al., 2004; Meldolesi et al., 2006; Mosaku et al., 2006; Zhao et al., 2008; Phabphal et al., 2009) had a sample size ranging from 37–106 and, therefore, low statistical power to detect an association between educational level and HRQoL. Six studies showed unemployment to be associated with poorer HRQoL.…”

Section: Resultsmentioning

confidence: 99%

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Predictors of health-related quality of life and costs in adults with epilepsy: A systematic review

et al. 2011

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SUMMARYPurpose: Given the high burden of epilepsy on both health-related quality of life (HRQoL) and costs, identification of factors that are predictive of either reduced HRQoL or increased expenditure is central to the better future targeting and optimization of existing and emerging interventions and management strategies for epilepsy. Methods: Searches of Medline, Embase, and Cochrane Library (up to July 2010) to identify studies examining the association between demographic, psychosocial, and condition-related factors and HRQoL, resource utilization or costs in adults with epilepsy. For each study, predictor factor associations were summarized on the basis of statistical significance and direction; the results were then combined across studies. Key Findings: Ninety-three HRQoL and 16 resource utilization/cost studies were included. Increases in seizure frequency, seizure severity, level of depression, and level of anxiety and presence of comorbidity were strongly associated with reduced HRQoL. The majority of studies were cross-sectional in design and had an overall methodologic quality that was judged to be ''moderate'' for HRQoL studies and ''poor'' for health care resource or costs studies. In the 53 multivariate studies, age, gender, marital status, type of seizure, age at diagnosis, and duration of epilepsy did not appear to be associated with HRQoL, whereas the predictive influence of educational and employment status, number of antiepileptic drugs (AEDs) and AED side effects was unclear. The association between predictive factors and HRQoL appeared to be consistent across individuals whether refractory or seizures controlled or managed by AEDs. There were insufficient multivariate studies (five) to reliably comment on the predictors of resource utilization or cost in epilepsy. Significance: In addition to seizure control, effective epilepsy management requires the early detection of those most at risk of psychological dysfunction and comorbidity, and the targeting of appropriate interventions. There is need for more rigorous studies with appropriate multivariate statistical methods that prospectively investigate the predictors of HRQoL, resource utilization, and costs in epilepsy.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Predictors of health-related quality of life and costs in adults with epilepsy: A systematic review

et al. 2011

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“…The social, economic and health impact of mental illness are far-reaching, where they are associated with excess all-cause mortality [2-4], work related disability [2, 4-6]. lower quality of life [7] and cardiovascular diseases risk [8-10]. Studies conducted in sub-Saharan Africa show that 20–30% of primary health clinic attendees present with depressive symptoms and other psychological disorders as the first or secondary reason for seeking medical care [11-13].…”

Section: Introductionmentioning

confidence: 99%

Prevalence and Correlates of Mental Distress Among Working Adults in Ethiopia

Gelaye¹,

Lemma²,

Deyassa³

et al. 2012

CPEMH

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Objective:To evaluate the prevalence of mental distress and its correlates among working Ethiopian adults.Methods:This cross-sectional study of 2,180 individuals (1,316 men and 864 women) was conducted among working adults in Addis Ababa, Ethiopia. A structured questionnaire was used to collect information on socio-demographic and lifestyle characteristics of participants. Mental distress was assessed using the self-reporting questionnaire (SRQ). Logistic regression was employed to estimate adjusted odds ratios (OR) and 95% confidence intervals (95% CI).Results:The prevalence of mental distress in the study sample was 17.7% (25.9% in women and 12.4% in men). Younger participants (age ≤24 years) had the highest prevalence of mental distress (35.5% in women and 16.7% in men). The odds of mental distress was 2.47-fold higher among women as compared with men (OR=2.47, 95% CI 1.97-3.09). Participants reporting excellent health status had a 50% reduced odds of mental distress (OR=0.47; 95%CI: 0.38-0.59); and moderate alcohol consumption was associated with a slight increased odds of mental distress (OR=1.26; 95%CI: 1.00-1.67).Conclusion:A high prevalence of mental distress was observed among working adults in Ethiopia. Our findings suggest that the workforce institutions should provide targeted prevention and intervention programs to improve the mental health state of their employees. National mental health policy that clearly outlines and addresses mental distress among working adults is also warranted.

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“…It is therefore a limited measure of disability in the narrower sense of this term, in that persons with disability can often be asymptomatic. It is best understood in this context as a measure of emotional distress (Ogundipe et al, 2014) or a proxy for quality of life (Mosaku et al, 2006), as it has been used in other African studies. Future research of this kind could employ the WHODAS 2.0 (World Health Organization, 2010), which focuses specifically on disability and has been used to generate utility scores for QALYs.…”

Section: Discussionmentioning

confidence: 99%

Cost-effectiveness of the Mental Health and Development model for schizophrenia-spectrum and bipolar disorders in rural Kenya

et al. 2015

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Authors' contributions: SR, CL, JK, MW, SKW and SM designed the study; VdM, MK, and DM proposed the framework for economic analysis; VdM conducted the analysis and drafted the article; all authors revised the article and approved the final version. Funding:The intervention was funded by the European Commission's Non-State Actor funding stream (DCI-NSAPVD/2008/156-918) and the UK Department for International Development's Civil Society Challenge Fund (CSCF 450).Competing Interests: Shoba Raja, Joyce Kingori, Milka Waruguru and Saju Mannarath are employees of BasicNeeds. Abstract (164 words)Background. The treatment gap for serious mental disorders across low-income countries is estimated to be 89%. The model for Mental Health and Development (MHD) offers community-based care for people with mental disorders in eleven low-and middle-income countries.

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Quality of Life and Associated Factors among Adults with Epilepsy in Nigeria

Abstract: Controlling seizures and paying attention to the psychological needs of adult epileptics will have a positive effect on the QOL among Nigerian epileptics.

Cited by 46 publications

References 37 publications

Predictors of health-related quality of life and costs in adults with epilepsy: A systematic review

Predictors of health-related quality of life and costs in adults with epilepsy: A systematic review

Prevalence and Correlates of Mental Distress Among Working Adults in Ethiopia

Cost-effectiveness of the Mental Health and Development model for schizophrenia-spectrum and bipolar disorders in rural Kenya

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