|Year : 2019 | Volume
| Issue : 9 | Page : 1180-1188
Health-related quality of life in people with chronic diseases managed in a low-resource setting – A study from South East Nigeria
UN Ijoma1, NN Unaogu2, TI Onyeka3, CB Nwatu1, CL Onyekonwu4, IO Onwuekwe1, F Ugwumba5, RC Nwutobo1, CV Nwachukwu6
1 Department of Medicine, College of Medicine, University of Nigeria, Ituku-Ozalla Campus, Enugu, Nigeria
2 Federal Neuropsychiatric Hospital, Enugu, Nigeria
3 Department of Anaesthesia/Pain & Palliative Care Unit, Multidisciplinary Oncology Centre, College of Medicine, University of Nigeria, Ituku-Ozalla Campus, Enugu, Nigeria
4 Sub-Department of Dermatology, Department of Medicine, College of Medicine, University of Nigeria, Ituku-Ozalla Campus, Enugu, Nigeria
5 Department of Surgery, College of Medicine, University of Nigeria, Ituku-Ozalla Campus, Enugu, Nigeria
6 Department of Medical Physiology, College of Medicine, University of Nigeria, Enugu Campus, Enugu, Nigeria
|Date of Acceptance||15-Apr-2019|
|Date of Web Publication||6-Sep-2019|
Dr. N N Unaogu
Federal Neuropsychiatric Hospital, Enugu
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Assessment of health-related quality of life (HRQOL) in resource-limited settings is critical to evaluate and improve the burden of morbidity and mortality associated with chronic medical disorders. There is a dearth of data on HRQOL among patients suffering from chronic medical disorders in Nigeria. This study assessed the HRQOL of participants with diabetes mellitus (DM), human immunodeficiency virus (HIV) infection, and cancer in a hospital setting with limited resources and highlighted associated factors. Methods: The WHOQOL-BREF instrument was used to study a cross section of the participants at the University of Nigeria Teaching Hospital, Enugu. Data were analyzed using Statistical Package for Social Sciences (SPSS). Results: The distribution of the 613 study population was diabetes mellitus 120, HIV 389, and various cancers 104. Majority (67.9%) earned less than $1 per day and only 7.5% had any form of health insurance. The HIV group had higher QoL scores. Younger age, higher educational status, being employed, and having a care giver were positively associated with higher QoL. Patients with no comorbidities (76.6%) had an overall higher QoL score. Conclusion: Majority of the patients living with chronic medical diseases in Enugu, Nigeria were poor, vulnerable, and without access to health insurance. People living HIV generally had better quality life than those with other health conditions. There is a huge unmet need for people living with chronic medical conditions in Nigeria, which require strategies to counteract.
Keywords: Chronic diseases, health-related quality of life, low-resource setting, south east Nigeria
|How to cite this article:|
Ijoma U N, Unaogu N N, Onyeka T I, Nwatu C B, Onyekonwu C L, Onwuekwe I O, Ugwumba F, Nwutobo R C, Nwachukwu C V. Health-related quality of life in people with chronic diseases managed in a low-resource setting – A study from South East Nigeria. Niger J Clin Pract 2019;22:1180-8
|How to cite this URL:|
Ijoma U N, Unaogu N N, Onyeka T I, Nwatu C B, Onyekonwu C L, Onwuekwe I O, Ugwumba F, Nwutobo R C, Nwachukwu C V. Health-related quality of life in people with chronic diseases managed in a low-resource setting – A study from South East Nigeria. Niger J Clin Pract [serial online] 2019 [cited 2019 Nov 13];22:1180-8. Available from: http://www.njcponline.com/text.asp?2019/22/9/1180/266161
| Introduction|| |
Chronic medical disorders tend to run a lifelong or near-lifelong course, thereby affecting an individual's emotional, economic, social, occupational, and general perception of well-being albeit more so in low- and medium-income countries where resource are limited. Health care priorities are currently centered not only around healthcare professional assessments but also on a patient's perception of his/her health-related general well-being. Health-related quality of life has in the past two to three decades become an area of clinical research interest in patients with chronic diseases that can no longer be overlooked.
Quality of life is an important component of life in persons suffering from chronic medical diseases. Patrick and Erickson in 1993 defined health-related quality of life (HRQoL) as the value assigned to duration of life as modified by the impairments, functional states, perceptions, and social opportunities that are influenced by disease, injury, treatment, or policy.
Effective assessment of HRQoL in resource-limited setting is critical to evaluate and improve the burden of morbidity and premature mortality associated with chronic medical disorders. A significant reduction in HRQoL has been noted in patients with chronic medical conditions such as hypertension compared with their normotensive counterparts  and dependent on end organ damage. Evidence exists to show that there is an inverse relationship between the number of morbidities and HRQoL.,, HRQoL reflects the contribution of a patient's disease state to his general well-being and a low HRQoL is associated with worsening morbidity and mortality.
Most studies on health-related quality of life have assessed single disease entities.,,
There is a dearth of published data on the HRQoL among patients suffering from chronic medical disorders in resource challenged settings. This study, thus, sets out to assess the HRQoL in an African setting with limited resource for patients with diabetes mellitus, HIV, and malignant diseases; to highlight the challenges; and to examine patterns and prospects.
| Materials and Methods|| |
Study setting and design
This is a questionnaire-based, descriptive, cross-sectional study set in the outpatient clinics of the University of Nigeria Teaching Hospital, Ituku-Ozalla, Enugu, South East Nigeria, the foremost regional public hospital providing tertiary health care.
Inclusion criteria were adult patients ≥18 years with a diagnosis of any of (i) cancer, (ii) diabetes mellitus with at least one chronic complication, or (iii) human immunodeficiency virus (HIV) infection already on highly active antiretroviral treatment (HAART), who were being managed as outpatients. The diagnosis of cancer was based on confirmed histology report. Diabetes mellitus (DM) was diagnosed based on the WHO criteria and a diagnosis of HIV infection was made based on two positive rapid tests or a third tie breaker. Patients with similar diagnoses who were on admission in the hospital were excluded from the study.
Patients who met the study criteria were consecutively recruited between October and December 2017 from the various relevant outpatient clinics. Written informed consent was obtained from all the participants.
Ethical clearance was obtained from the Hospital's Research and Ethics Committee.
The WHOQOL-BREF was used for the assessment of HRQoL in this study. The WHOQOL-BREF is an abridged and practical form of the WHOQOL-100, which tests four domains: domain 1, physical health; domain 2, psychological; domain 3, social relationships; and domain 4, environment. It is an international, cross-cultural, and generic quality-of-life instrument that provides a comparison of different disease conditions and not necessarily specific to any disease or intervention. The four domain scores denote an individual' perception on quality of life in each particular domain. Scores are graded in a positive linear direction with higher scores denoting higher quality of life. Mean scores are eventually multiplied by 4 to make the domain scores comparable to the standard WHOQOL-100. The WHOQOL-BREF is made up of 26 questions with 2 questions on general quality of life and 24 questions spanning the 4 domains.
Socioeconomic and demographic data and clinical evaluation were evaluated with a different questionnaire. The study instruments were administered by research assistants under the supervision of the researchers.
Data obtained were analyzed using IBM SPSS version 22.0 (Chicago, IL). Descriptive statistics were used to compute means and standard deviations for numerical variables as well as frequencies for nominal and ordinal variables. Significance of association between various variables and QoL was tested using the Chi-square test (χ2). Inferential statistics applied included an independent sample's t-test for the hypothesis and in comparing numerical sociodemographic variables. Analysis of variance was used in comparing mean QoL scores and a stepwise (forward) regression analysis to determine variations in mean QoL as explained by the joint predictive power of the variables. A P < 0.05 was considered statistically significant.
| Results|| |
In total, 613 participants were enrolled into the study. About 120 had diabetes mellitus, 389 had HIV and were on HAART, whereas 104 had a diagnosis of cancer. All patients were of the Igbo tribe. Males were 204 (33.3%) and females were 409 (66.7%) with a male: female ratio of 1: 2. Majority of the participants (71.1%) were between 26 and 55 years of age. Approximately, 63% of all participants were married and the vast majority were Christian (605, 98.7%). A minority (15.5%) of all the participants had no income at all and were completely dependent on others, whereas 321 (52.4%) earned less than N10,000.00 naira (USD 28.00) monthly. Only 46 (7.5%) of all participants had any form of medical insurance, with 45 of them on the National Health Insurance Scheme (NHIS) of the Nigerian Federal government. The rest of the sociodemographic data is detailed in [Table 1]a. [Table 1]b shows the mean number of dependents and number of hospitalizations of the study participants.
The transformed scores were used in this study. The transformed scores are the WHOQoL-BREF mean score multiplied by 4 to transform them to the WHOQoL-100. Participants with HIV had higher mean scores for domains 1 (physical health) and 3 (social relationships) (75.6 ± 14.3 SD and 72.5 ± 18.4 SD, respectively), whereas those with cancers had higher mean scores in domains 2 (psychological) and 4 (environment) (76.5 ± 13.7 SD and 69.3 ± 13.1 SD, respectively). Statistical significance was reached in domains 1, 2, and 4 (P value < 0.01) See [Table 2].
|Table 2: Comparison of quality of life among patients with diabetes mellitus, HIV, and cancer|
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As shown in [Table 3], females recorded higher QoL mean scores in physical health domain and psychological domain (71.5 ± 15.5 SD and 74.3 ± 14.1 SD, respectively). The QoL mean score was slightly higher in males than females in social relationships domain (71.4 ± 19.1 SD vs 71.2 ± 17.7 SD). In the environment domain, the QoL mean score was higher in male than females (66.7 ± 14.4 SD vs 63.2 ± 15.5 SD). Statistical significance was recorded in psychological and environment domains (P = 0.009 and P = 0.007, respectively).
|Table 3: Association of gender with the scores of the domains of quality of life among patients with chronic medical conditions n=613|
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Univariate regression analysis demonstrates the association of QoL with age, occupation, marital status, and highest level of education attained among the study participants. Highest mean QoL scores were seen in the age group of 26–35 years (76.3 ± 15.6 SD) and the lowest in the age group of >65 years (59.8 ± 18.2 SD). Scores for environment domain were, however, highest in the age group of >65 years (68.1 ± 14.4 SD). Statistical significance was attained in physical health domain (P < 0.001) and in psychological health domain (P value 0.046). Regarding association of QoL with occupation and highest level of education, statistical significance was noted in physical health domain only in both cases (<0.001). The highest scores were noted in professionals (75.0 ± 16.1SD) and in secondary school graduates (73.3 ± 14.8 SD). No significant relationship was established between QoL and marital status in physical health and psychological domains (P = 0.419 and P = 0.597, respectively). Highest mean QoL scores were obtained in domains 3 and 4 from the married participants (73.3 ± 17.0 SD and 65.7 ± 15.3 SD), both reaching statistical significance (P = 0.011 and P = 0.001, respectively) [Table 4], [Table 5], [Table 6], [Table 7], [Table 8].
|Table 4: Association of age with the scores of the domains of quality of life among patients with chronic medical conditions n=613|
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|Table 5: Association of occupation with the scores of the domains of quality of life among patients with chronic medical conditions n=613|
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|Table 6: Association of marital status with the scores of the domains of quality of life among patients with chronic medical conditions n=613|
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|Table 7: Association of level of education with the domains of quality of life among patients with chronic medical conditions n=613|
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|Table 8: Association of the presence of comorbidities with the scores of the domains of quality of life among patients with chronic medical conditions n=613|
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Participants who did not have comorbidities (470, 76.6%) displayed a higher mean QoL score in physical health, psychological health, and social relationship domains, with a positive test of significance (73.2 ± 15.1 SD, P < 0.001; 74.8 ± 13.9 SD, P < 0.001; and 72.4 ± 17.6 SD, P = 0.007, respectively) as seen in [Table 8]. [Table 9] shows a positive test of significance between the 530 (86.5%) participants who had caregivers and the 83 (13.5%) who had no caregivers ( P < 0.001). Female gender, age of the caregiver, and the relationship with the study participant all proved to be important factors ( P < 0.001 for all parameters).
| Discussion|| |
This is probably the first simultaneous study on health-related quality of life among patients with chronic diseases in South East Nigeria. Few studies on HRQoL exist in South East Nigeria, and dealt mostly with specific diseases.,, This applies also to studies from other parts of the country.,,,
Based on a validated study of HRQoL in a South West Nigerian community, a mean score of ≥78 in the WHOQOL-BREF is regarded as acceptable and indicative as good quality of life.
Sub-Saharan Africa has remained in the low category in the last three decades with a human development index still <0.55. High population and population growth rate, low population literacy, high dependency rate, and low total life expectancy rate all contribute to this low index. The Nigerian Gross Domestic Product (GDP), which measures the nation's investment output for a stipulated period, usually annually stands at 376.28 billion USD and a GDP per capita income of 1,994 USD in 2017. This stands in sharp contrast to developed countries with high GDP and per capita (USA: 19.931 billion and 59,501 USD, respectively; Luxembourg: 62.4 billion and 105,803 USD, respectively; Germany: 3,685 billion and 44, 549 USD, respectively).
In this study, participants who had HIV and were on HAART comparatively recorded higher QoL mean scores in all but social relationship domain than those with DM or cancers. We also noted that female gender impacted positively on physical health (domain 1), psychological health (domain 2), and social relationship (domain 3) but not on environment (domain 4). This is in keeping with previous studies done in other parts of the world. A Chinese study involving healthy medical students recorded higher mean scores in males in D1 and D2. Participants in this study were healthy younger medical students and this may account for this difference. Younger age group, having an occupation, being married and attainment of education higher or equal to secondary education were all noted to enhance QoL mean scores. This finding agrees with earlier research studies that unemployment and low socioeconomic status are associated with poor HRQOL.,,
Our study noted that the presence of comorbidities significantly affected all domains except for environment. Chronic diseases have a strong negative impact on patients' QoL., However, differences may be seen, depending on the specific disease entities. The study is in line with that of Xu et al., which stated that the impact on patients' HRQoL may vary depending on the different types of chronic diseases that patient had.
A high proportion of participants had caregivers, who were mostly family members. These individuals recorded a significantly higher QoL. The family structure seen in Africa and particularly in the Igbo tribe of South East Nigeria makes for such social support, which engenders stability and improved overall well-being. The family social system in Nigeria and African as a whole has not yet been completely eroded by westernization and this tends to improve QoL.,, Studies in other parts of the world also support the improved QoL among people with chronic illnesses and a strong family support.,
Of all the study participants, 67.8% earn below $1 per day and only a small number (7.5%) had any form of insurance. This means that health expenditures occur at the point of service and is out-of-pocket. It is noted that catastrophic health expenditure (CHE) is increased in settings where out-of-pocket payment for health is prevalent. Onoka et al. working in the same region in Nigeria found significantly higher values of CHE than recorded in other developing countries. Out-of-pocket payment as a method of health financing has been found to adversely affect provision of health care and overall perceived quality of life.
| Conclusion|| |
We conclude from our study that mean scores for HRQOL is reduced in patients with chronic diseases (HIV, DM, and cancers) in all domains. Presence of other comorbidities adversely affects the HRQOL mean scores, whereas the presence of caregivers and family support were positive associations of HRQOL. Nigeria is still grappling with a poor financing health structure as majority of the participants lacked any form of medical insurance and were paying out-of-pocket at the point of service.
| Limitations|| |
The instrument used (WHOQOL-BREF), though validated in Nigeria, was not translated into the language of South East Nigeria, Igbo. Though none of the respondents reported any difficulty in comprehending the questionnaire, such a translation may have enhanced more complete grasp.
The authors wish to thank the doctors and nurses in the medical and surgical outpatient clinics of the University of Nigeria Teaching Hospital, Ituku-Ozalla, Enugu, who cooperated with this research effort.
All authors participated in the conceptualization of the study and collaborated in the design. NRC and NC collected the data. UN oversaw the data analysis. IUN, UN, and OI wrote the manuscript, whereas all authors reviewed and approved the final draft. Funding was contributed to by the authors. OI is the guarantor of the manuscript.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Megari K. Quality of life in chronic disease patients. Health Psych Res 2013;e27:141-8.
Patrick DL, Erickson P. Health Status and Health Policy: Quality of Life in Health Care Evaluation and Resource Allocation. New York: Oxford University Press; 1993. p. 7.
Wang R, Zhao Y, He X, Ma X, Yan X, Sun Y, et al.
Impact of hypertension on health-related quality of life in a population based study in Shanghai, China. Public Health 2009;123:534-9.
Heyworth ITM, Hazell ML, Linehan MF, Frank TL. How do common chronic conditions affect health-related quality of life? British J Gen Pract 2009;159:e353-8.
Wang H, Beyer M, Genshichen J, Gerlach M. Health-related quality of life among general practice patients with differing chronic diseases in Germany; Cross sectional survey. BMC Public Health 2008;8:246.
Langebeek N, Kooji KW, Wit FW, Stolte IG, Sprangers MAG, Reiss P, et al.
Impact of comorbidities and ageing on health-related quality of life in HIV-positive and HIV-negative individuals. AIDS 2017;10:1471-81.
Shavro SA, Ezhilarasu P, Augustine J, Bechtel JJ, Christopher DJ. Correlation of health-related quality of life with other disease severity indices in Indian chronic obstructive pulmonary disease patients. Int J Chron Obstruct Pulmon Dis 2012;7:291-6.
Soni RK, Weisbord SD, Unruh ML. Health-related quality of life outcomes in chronic kidney disease. Curr Opin Nephrol Hypertens 2010;19:153-9.
Rwegerera GM, Moshomo T, Gaenamong M, Oyewo TA, Gollakota S, Rivera YP, et al.
Health related quality of life and associated factors among patients with diabetes mellitus in Botswana. Alexandria J Med 2018;54:111-8.
The WHOQOL Group. The World Health Organization Quality of Life Assessment (WHOQOL): Development and general psychometric properties. Soc Sci Med 1998;46:1569-85.
Onwuekwe IO, Unaogu N, Aguwa EN, Ezeala-Adikaibe B. Health-related quality of life and its determinants in adult Nigerians with epileptic seizures. Austin J Neurol Disord Epilepsy 2015;2:1013.
Akosile CO, Adegoke B, Ezeife CA, Maruf FA, Ibikunle PO, Johnson OE, et al.
Quality of life and sex differences in a south-eastern Nigerian stroke sample. Afr J Neurol Sci 2013;13:19-25.
Ayuk AC, Oguonu T, Ikefuna AN, Ibe BC. Health-related quality of life in school-aged children with and without asthma in Enugu, South East Nigeria. Niger J Pediatrics 2013;40:364-9.
Ibrahim A, Mubi B, Omeiza B, Wakil M, Rabbebe I, Jidda M, et al.
An assessment of depression and quality of life among adults with Diabetes Mellitus in the University of Maiduguri Teaching Hospital. Internet J Psychiatry 2013;2:1-15.
Ooni OD, Aina OF, Ojini FI, Olisah VO. Quality of life and associated factors among post stroke clinic attendees in a University Teaching Hospital in Nigeria. Niger Med J 2016;57:290-8.
Jaiyesimi AO, Sofela EA, Rufai AA. Health related quality of life and its determinants in Nigerian breast cancer patients. Afr J Med Med Sci 2007;36:259-65.
Raji MO, Liman HM, Raji IA, Kaoje AU. Health-related quality of life of people living with HIV/AIDS accessing care in a tertiary health-care centre in North West Nigeria. Sahel Med J 2017;20:149-54. [Full text]
Akinyemi OO, Owoaje ET, Popoola OA, Ilesanmi OS. Quality of life and associated factors among adults in a community in South West Nigeria. Ann Ibd Pg Med 2012;10:34-9.
Human Development progress report 2016. Available from: http://hdr.undp.org/
. [Last accessed on 2018 Aug 24].
IMF: World Economic Outlook (WEO) Database. April 2018. Available from: www.imf.org/exxternal/datamapper/index.php. [Last accessed on 2018 Aug 24].
Zhang Y, Qu B, Lun S, Wang D, Guo Y, Liu J. Quality of life of medical students in China: A study using the WHOQOL-BREF. PLoS One 2012;7:e49714.
Cheng L, Cumber S, Dumas C, Winter R, Nguye KN, Nieman LZ. Health related quality of life in pre-geriatric patients with chronic diseases at urban public support clinics. Health Qual Life Outcomes 2003;1:63.
Dally EJ, Trivedi MH, Wisniewski SR, Nierenberg AA, Gaynes NB, Warden D, et al.
Health-related quality of life in depression: A STAR*D report. Ann Clin Psychiatry 2010;22:43-55.
McDaid O, Hanly MJ, Richardson K, Kee F, Kenny RA, Savva GM. The effect of multiple chronic conditions on self-rated health, disability and quality of life among the older populations of Northern Ireland and the Republic of Ireland: A comparison of two nationally representative cross-sectional surveys. BMJ Open 2013;3. pii: e002571. doi: 10.1136/bmjopen-2013-002571.
Ganes Kumar S, Anindo M, Pavithra G. Quality of life (QOL) and its associated factors using WHOQOL-BREF among elderly urban Pondicherry, India. J Clin Diagnostic Res 2014;1:54-7.
Xu RH, Cheung AWL, Wong EL. Examining the health-related quality of life using EQ-5D-5L in patients with four kinds of chronic diseases from specialist outpatient clinics in Hong Kong SAR, China. Patient Prefer Adherence 2017;11:1565-72.
Fatusin A, Agboola SM, Shabi OM, Bello IS, Elegbede OT, Fatusin BB. Relationship between family support and quality of life of type 2 diabetes mellitus patients attending family medicine clinic, Ido-Ekiti. Nigerian Journal of Family Practice 2016;7:3-11.
Gureje O, Kola L, Afolabi E, Olley B. Determinants of quality of life of elderly Nigerians: Results from the Ibadan study of ageing. Afr J Med Med Sci 2008;37:239-47.
Belanger E, Ahmed T, Vafaei A, Curcio CL, Phillips SP, Zunzunegui MV. Sources of social support associated with health and quality of life: A cross-sectional study among Canadian and Latin American older adults. BMJ Open 2016;6:e011503.
Kaur H, Kaur H, Venkatesshan M. Factors determining family support and quality of life of elderly population. Inter J Med Sci Pub Health 2015;8:1049-53.
Puteh SEW, Almualm Y. Catastrophic health expenditure among developing countries. Health Syst Policy Res 2017;4:1.
Onoka CA, Onwujekwe OE, Hanson K, Uzochukwu BS. Examining catastrophic health expenditures at variable thresholds using household consumption expenditure diaries. Trop Med Inter Health 2011;10:1334-41.
Uzochukwu BSC, Ughasoro MD, Etiaba E, Okwuosa C, Envuladu E. Health care financing in Nigeria: Implications for achieving universal health coverage. Niger J Clin Pract 2015;18:437-44.
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[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7], [Table 8], [Table 9]