Quality of life and its sociodemographic and clinicalpredictorsamong people on antiretroviral therapy (ART) at a resource-limited clinic.

IOSR Journal of Dental and Medical Sciences (IOSR-JDMS)
e-ISSN: 2279-0853, p-ISSN: 2279-0861.Volume 14, Issue 11 Ver. VII (Nov. 2015), PP 73-81
www.iosrjournals.org
DOI: 10.9790/0853-141177381 www.iosrjournals.org 73 | Page
Quality of life and its sociodemographic and
clinicalpredictorsamong people on antiretroviral therapy (ART)
at a resource-limited clinic.
Ndaimani Augustine1
, Nyamakura Rudo2
, Zvinavashe Mathilda3
, Haruzivishe
Clara4
, Mukona Doreen5
, Mhlanga Maxwell6
1-6
(Department of Nursing Science, University of Zimbabwe College of Health sciences, Zimbabwe)
Abstract: Improved life expectancy of people on antiretroviral therapy has increased focus on quality of life
issues. The objectives of this study were to assess the quality of life in people on antiretroviral therapy;
determine the sociodemographic and clinical predictors of quality of life in people on antiretroviral therapy and
to evaluate the reliability of the World Health Organization Quality of Life BREF (WHOQOL BREF)
instrument. The study was conducted using a descriptive correlational survey at Masvingo Provincial Hospital
Opportunistic infections (OI) Clinic.A randomly selected sample of 300 participants, on antiretroviral drugs
was interviewed through standardized interviewing. The interview schedule had 36 items, inclusive of the 26-
item WHOQOL BREF.Transformed qualities of life were: Domain 1 (Mean = 67.2, SD = 16.08) followed by
Domain 2 (Mean = 65.56; SD = 16.11), Domain3 (Mean = 63.83; SD = 19.30) and, lastly, Domain 4 (Mean =
55.84; SD = 16.71). The mean transformed overall quality of life score was 63.11 (SD = 14.06). Statistically
significant positive correlates for quality of life included being male, a period of more than 3 years on ART,
monthly income above US$250 and Islam religion. Statistically significant negative correlates of quality of life
included being an urban dweller, being single, unemployed, a pensioner or a traditionalist. The coefficients of
determination for the predictors was r2
= 0.19, r2
= 0.22, r2
= 0.23 and r2
= 0.31 for domain 1, 2, 3 and 4
respectively. There was no significant linear relationship between quality of life and respondends’CD4 count.
The Cronbach’s alpha for the WHOQOL BREF instrument was 0.92. More interventions need to be done for
urban dwellers, single individuals, pensioners, unemployed people and traditionalists on ART to improve their
quality of life. Quality of life should not be extrapolated from the patient’s CD4 count dynamics alone, but
should rather be determined separately. The WHOQOL BREF is reliable for monitoring quality of life of
individuals on ART.
Key words: Antiretroviral therapy, Human immunodeficiency virus (HIV), Quality of life, Sociodemographic,
WHOQOL BREF.
I. Introduction
With the 42% decrease in AIDS-related deaths between 2004 and 2015, and increased life expectancy
of people on antiretroviral therapy from 36 years (2001) to 55 years (2014), albeit at a cost of US$21.7 through
the Global response to HIV and AIDS there is an increasing emphasis on quality of life in people living with
HIV, rather than mere survival. The global AIDS response reduced AIDS related deaths to about 1.2 million
annually(1)
. Quality of life is becoming one of the most important outcome and many people commit to
antiretroviral therapy to improve it(2-6)
. Quality of life refers to an individual’s perception of their standing in life
with respect to what they expect in life according to their norms and values, including happiness and satisfaction
with life. It involves personal satisfaction in the way in which an individual lives(7-9).
This generally implies that
quality of life is optimal when a person’s happiness and comfort needs are met. Changes in World Health
Organization (WHO) guidelines on antiretroviral therapy (ART) result in more and more people living with HIV
and AIDS being commenced and maintained on lifelong ART regardless of their CD4 count, depending on
sustainability(10-12)
.Of the 36.9 million people living with HIV, AIDS, 15 million are already on antiretroviral
therapy. Antiretroviral therapy has dramatically improved life expectancy of people living with HIV & AIDS
(2;13)
.As life expectancy increases due to ART, people living with HIV & AIDS are becoming more concerned
with better quality of life. Factors associated with reduced quality of life include female gender, side effects of
ART, opportunistic infections, low level of education, poverty, low level of social interaction, CD4 count below
200 cells/mm3
and old age (14-17)
Increased quality of life has been shown to be associated with a CD4 above 500
cells/mm3
, support from significant others, male gender or an annual income of more than US$20 000(14;16;18)
.
Documented studies mainly measured quality of life, in middle and high income countries prior to the recent
changes in ART guidelines (19)
. Considering the importance of quality of life in ART, the fact that 71% of
people living with HIV & AIDS live in low income Sub-Saharan Africa it was necessary to determine the
quality of life, particularly at resource limited clinic in Zimbabwe which is a low income country. More so, there

Quality of life and its sociodemographic and clinicalpredictorsamong people on antiretroviral...
was a need to assess quality of life in light of recent changes in WHO ART guidelines. This study sought to
determine the quality of life among people on ART, using the WHOQOL BREF, and its sociodemographic
correlates.
II. Materials And Methods
The study was carried out through a cross-sectional survey on PLWHA who attended to Masvingo
Provincial Hospital opportunistic infections (OI) clinic for their scheduled and consultation visits. The Hospital
is a public tertiary referral health centre for Masvingo Province which is divided into 7 districts and a population
of 1.5 million people. A sample of 300 participants was recruited for the study based on systematic sampling.
The sample size was calculated using the Dobson formula, to achieve a power of 0.8, effect size of 0.5 and 95%
precision of estimate, and a possible attrition rate of 20%. Data was collected through standardised interviews
using a 36-item interview schedule. The interview schedule had 2 sections: section A with 10 closed ended
items on demographic and clinical data and section B with 26 items constituting the WHOQOL BREF Field
Trial Version. The tool has 26 items, 3 of which are reverse scored. The first 2 items pertain to overall perceived
quality of life. Domain 1 has 7 items relating to physical health, domain 2 has 6 items concerning psychological
well-being, domain 3 has 3 items relating to social relationships and, lastly, domain 4 has 8 items pertaining to
the patient’s environment. Raw scores in the 4 quality of life domains are transformed using tables provided
with the instrument (20)
. The WHOQOL BREF was tested in many countries, including Zimbabwe, and
demonstrated an internal consistency ranging between 0.63 and 0.86 (14;16;21-23)
. The content validity of the items
in section was improved by having the instruments examined by researchers from the University of Zimbabwe
College Of Health Sciences and clinicians at the study site. The instrument was pre-tested on 5 respondents to
check and improve the order and clarity of the items. Data was collected over 8 weeks from 14 April to 6 June
2013 between 8:00am and 15:00pm. The study was approved by the Joint Research Ethics Committee for the
University of Zimbabwe College of Health Sciences and Parirenyatwa Group of Hospitals and the Medical
Research Council of Zimbabwe. Signed consent was also sought from participants before each interview after
an explanation of the study was done to the respective participants. Anonymous coded data was stored in a
lockable drawer. The data was analysed, using Stata 13, through descriptive statistics and multiple linear
regression using the sociodemographic and clinical factors as predictors and each of the 4 quality of life
domains as the outcome. An overall transformed quality of life score was computed by averaging the scores
from the 4 domains.
III. Results
There were 177 (59%) females from the sample of 300 respondents. The age of the respondents was
normally distributed with a mean of 40.9 (9.5). Table 1 is a summary of other demographic features of the
participants. The married, 143 (47.7%) formed the bulk of the sample. Most participants, 189 (63%) had
secondary school education as their highest level of education while 6 (2%) had never attended formal school.
There were more participants staying in rural areas; 158 (52.5%) compared to Masvingo urban 142 (47.3%).
The participants were prominently unemployed, 118 (39.3%); 84 (28%) were self-employed. Two hundred and
forty two (80.7%) had a monthly income ranging between zero and US$250. The majority, 271 (90.3%) were
Christians while 3 (1%) were of Guta RaMwari religion. Lastly, 105 (35%) had been on ART for a successive
period of more than 3 years. One hundred and twenty four (41.4%) had been on ART for a year or below.

Table I: Demographic Characteristics (N=300)
Sociodemographic characteristic Frequency Percentage
Marital status
Married 143 47.7
Single 55 18.3
Divorced 24 8.0
Widowed 64 21.3
Cohabitating 14 4.7
Level of Education
Never 6 2.0
Primary 75 25.0
Secondary 189 63.0
Tertiary 30 10.0
Place of Residence
Urban 142 47.3
Rural 158 52.7
Employment Status
Formally employed 65 21.7
Self employed 84 28.0
Student 21 7.0
Pensioner 12 4.0
Unemployed 118 39.3
Monthly income in US$
0 to 250 242 80.7
251 to 600 41 13.7
Above 600 17 5.7
Religion
Christianity 271 90.3
Traditionalist 21 7.0
Islam 5 1.7
Other 3 1.0
Period on ART
Below 3 months 38 12.7
3 to 12 months 86 28.7
1 year to 3 years 71 23.7
Above 3 years 105 35.0
Fig. I below shows that the CD4 count was positively skewed in both males and females although males
generally had lower CD4 counts compared to their female counterparts. The median CD4 for males was 88
cells/mm3
(IQR = 142) while for females it was 96 cells/mm3
(IQR = 160).

Figure I: Box Plots Of Respondents’cd4 Count
Quality of life scores are summarized in Table II. The WHOQOL BREF yielded a Cronbach’s Alpha of
0.92. Quality of life scores for the 4 domains and the total transformed Quality of life were normally distributed.
Highest quality scores were achieved for Domain 1 (Mean = 67.2, SD = 16.08) followed by Domain 2 (Mean =
65.56; SD = 16.11), Domain3 (Mean = 63.83; SD = 19.30) and, lastly, Domain 4 (Mean = 55.84; SD = 16.71).
The mean transformed overall quality of life score was 63.11 (SD = 14.06). All the means were statistically
significant.
Table Ii: Participants’ Transformed Scores For Domain 1 (Physical Health): (N=300).
Variable Frequency Percentage
Domain 1 transformed score
0 – 25 7 2.3
26 – 50 33 11.0
51 – 75 166 55.3
76 – 100 94 31.3
0 – 25 10 3.3
26 – 50 43 14.3
51 – 75 183 61.0
76 – 100 64 21.3
0 – 25 21 7.0
26 – 50 73 24.3
51 – 75 142 47.3
76 – 100 64 21.3
0 – 25 15 5.0
26 – 50 111 37.0
51 – 75 148 49.3
76 – 100 26 8.7
Total Transformed score
0 – 25 6 2.0
26 – 50 51 17.0
51 – 75 185 61.7
76 – 100 58 19.3
Total 300 100
0
100200300400
CD4COUNT
female male

Table III summarizes linear regression coefficients of predictors of quality of life Domains 1 to 4. The
coefficients of determination were Domain 1: (r2
= 0.19, F (23; 276) = 2.85; p>F = 0.000), Domain 2: (r2
=0.22.
F (23; 276) = 3.34, p>F = 0.000), Domain 3: (r2
= 0.23, F (23, 276) = 3.65, p>F = 0.000) and Domain 4:
(r2
=0.31, F (23, 276) = 5.55; p>F = 0.000). Only statistically significant correlates are shown. Positive predictors
of quality of life include male sex, being on ART for more than 3 years, monthly income above US$250 and
Islam religion. Negative predictors of quality of life included residence in an urban area, being single,
unemployed, a pensioner and traditionalist.
Table Iii: Regression Coefficients For Predictors Of Quality Of Life Domains
Predictor Slope Standard error 95% confidence
interval
Domain 1: Physical health
Sex
Female Reference
Male 4.25 2.09 0.13; 8.37
Place of residence
Rural Reference
Urban -5.50 1.92 -9.28; -1.71
Period on ART
1 – 3 years Reference
Above 3 years 8.83 2.51 3.89; 13.76
Intercept 74.30 10.56 53.50; 95.10
Domain 2: Psychological well being
Marital status
Cohabitating Reference
Single -12.82 4.76 -22.20; -3.46
Place of residence
Rural Reference
Urban -6.50 1.90 -10.23; -2.77
0 – 250 Reference
251 – 600 7.82 2.96 2.00; 13.64
Religion
Christianity Reference
Islam 15.50 7.43 0.86; 30.10
Period on ART
Above 3 years 9.19 2.47 4.33; 14.06
Intercept 66.61 10.42 46.10; 87.12
Domain 3: Social relations
Sex
Male 9.19 2.45 4.38; 13.01
Marital status
Cohabitating Reference
Single -21.51 5.64 -32.61; -10.40
Constant 65.49 12.36 41.16; 89.81
Domain 4: Environment
Employment
Formally employed Reference
Unemployed -10.07 2.64 -15.27; -4.88
Pensioner -15.45 4.87 -25.03; -5.87
0 – 250 Reference
251 – 600 6.76 2.87 1.11; 12.40
Above 600 8.98 3.99 4.88; 15.27
Religion
Christianity Reference
Traditionalist -13.67 3.89 -21.33; -6.00
Other 26.85 8.99 9.15; 44.56
Period on ART
Above 3 years 7.89 2.40 3.17; 12.61
Intercept 58.66 10.10 38.77; 78.55
Table IV below summarizes the multiple linear regression of sociodemographic predictors of overall
transformed quality of life. The coefficient of determination was 0.23, implying that the sociodemographic
factors were responsible for 23% of the variation in quality of life. The coefficient was significant, with F (23,
276) = 3.75 (p=0.00). Compared to females, males had a generally better quality of life (β = 4.46; SEB =
1.78). Being single was associated with a reduction in overall quality of life (β = -9.31; SEB = 4.10) compared
to cohabitating. Although cohabitation promised to be associated with a better overall quality of life compared

to married, widowed and divorced people, the results were not statistically significant. In terms of religion,
being a traditionalist was associated with a reduction in quality of life (β = -7.36; SEB = 3.46). Lastly, being on
antiretroviral therapy for more than 3 years was associated with an increase in quality of life, compare to being
on ART for 1 to 3 years. A post hoc analysis showed that an income of $251 - $600 positively correlated with
the psychological domain of quality of life (β = 5.86; SEB = 2.71; CI = 0.53; 11.19) and the environmental
domain (β = 11.05; SEB = 2.71; CI = 5.72; 16.38). A monthly income above $600 was associated with a high
environmental quality of life (β = 14.8; SEB = 4.03; 6.89; 55.51) (not shown). The model intercept was 66.26
(SEB = 8.97; 95%CI = 48.60; 83.92). Other sociodemographic predictors are shown although they were not
statistically significant.
Table Iv: Linear Regression Coefficients For Predictors Of Overall Transformed Quality Of Life
Predictor Slope Standard error 95% CI
Age 0.04 0.10 -1.54; 0.23
CD4 Count 0.01 0.01 -0.011; 0.02
Sex
Female 1
Male 4.46 1.78 0.96; 7.96
Marital status
Cohabitating 1
Married - 0.86 3.78 -8.29; 6.58
Divorced - 0.95 4.51 -9.83; 7.93
Widowed - 1.25 4.08 -9.28; 6.77
Single - 9.31 4.10 -17.37; -1.24
Level of Education
Never attended school 1
Secondary -3.73 6.04 -15.62; 817
Primary -6.60 5.91 -18.23; 5.05
Tertiary -10.14 6.81 -23.54; 3.26
Area of residence
Rural 1
Urban -4.13 1.63 -7.34; -0.92
Employment
Formally employed 1
Student -0.13 4.19 -8.38; 8.12
Pensioner -3.12 4.32 -11.63; 5.39
Unemployed -4.58 2.34 -9.19; 0.03
Self-employed 1.87 2.41 -2.87; 6.81
Income in US$
0 – 250 1
Above 600 2.83 3.54 -4.14; 9.80
251 – 600 4.35 2.55 -0.67; 9.36
Religion
Christianity 1
Traditionalist -7.36 3.46 -14.17; -0.55
Islam 9.36 6.40 -3.23; 21.95
Other 12.71 7.99 -3.00; 28.43
Period on Antiretroviral therapy
1 – 3 years 1
Below 3 months -0.43 2.89 -6.12; 5.26
3 – 12 month 1.38 2.28 -3.11; 5.86
Above 3 years 7.62 2.13 4.43; 11.81
Constant 66.26 8.97 48.60; 83.92
IV. Discussion
The sample of 300 participants had enough statistical power, results of the current study can be safely
extrapolated to the population(24)
.The mean age of 40.8 years and modal age of 41 years was consistent with
other studies on the same subject and the Zimbabwean demographic profile(25)
. The 59% of the respondents
were female, a figure slightly higher than ZDHS figures which estimated that 53.8% of people living with HIV
& AIDS were female, the rest being male (25)
. There are 691 350 males and 795 254 females in Masvingo26.
The disproportionate gender prevalence of HIV may also be attributed to poor capability of females in
Masvingo to negotiate for safer sex with their male partners. Moreover, since 92% of HIV in Zimbabwe is
through sexual intercourse, females are more at risk of infection due to their anatomy and the fact that they are
receptive during sexual intercourse. In the present study 47.7% participants were married. This figure is lower
than the 59% national census figure for Masvingo and the 76.6% for a similar study in China(25;26)
. This may
imply that married people in Masvingo are less vulnerable to HIV infection since more unmarried people were
in the sample. Alternatively it may imply that there is poor spousal support in HIV & AIDS management and
few married people are reluctant to enter the HIV treatment cascade. Only 2% had no formal education. This is

commensurate with the high literacy levels in Zimbabwe(27)
. Thus most participants could understand and
possibly make use of HIV-related public health education campaigns. High knowledge levels might translate to
positive living which may improve some quality of life domains. However the national Census found that 13%
in Masvingo had never attended school (26)
. The disparity with the current findings may have been because most
of the participant were relatively young, hence, could have been exposed to either formal education or adult
literacy classes which were common soon after independence, 1980. A post-hoc analysis showed that 99% were
aged 65 years or below. That was consistent with the current life expectancy of people on ART. In the current
study 47.3% stayed in urban areas while 52.7% stayed in rural areas. The province is reported to have 90% of its
populace residing in rural areas (26)
.Thus, Masvingo urban dwellers are more vulnerable to HIV infection
compared to their rural counterparts. Thirty-five percent had been on ART for more than 3 years, 23.7%
between 1 and 3 years, 28.7% for 3 to 12 months and 12.7% below 3 months. The findings are below other
reported findings. (28)
. This may be explained by an intensified ART scale-up in Zimbabwe and ART coverage
which recently was increased to cover PLWHA with a CD4 below 350 cells/mm3
up from a CD4 count below
200 cells/mm3
. Hence, more PLWHA who had taken ART for less than one year(19;29)
. Another explanation may
be because of high AIDS related mortality during the country’s recession from 2000 to 2008.In this study,
74.3% had a CD4 count below 200 cells/mm3
. The mean CD4 count was 135.5 cells/mm3
. CD4 levels were
lower than in other similar studies(16)
and corresponded with severe immunosuppression(19)
. During the time of
data collection some centres were commencing people on ART based on WHO clinical staging, due to shortage
of CD4 count machines. The shortage of the machines also implied that people could take long before
rechecking CD4 count during which time it could drastically fall before they could get commenced on
ART.Also, late commencement of people on ART may have stemmed from denial, stigma, faith-related issues,
financial constraints, particularly prior to decentralisation of HIV & AIDS services.
4.2 Quality of life
Transformed WHOQOL BREF scores range from 0 to 100. In the current study, the mean transformed
quality of life was 67.2 for the physical domain, 65.6 for the psychological well-being domain, 68.3 for the
social relationships domain and 55.8 for the environmental domain. The values are relatively higher than
previous findings(30)
. For, instance, in India the mean quality of life score were 47.63 for environmental domain,
47.4 for the psychological well-being domain, 46.37 for the physical health domain and 43.37 for the social
relationships domain(18)
. The discrepancy may be attributed to enhanced social support through peer social
groups, availability of treatment partners and the presence of a local non-governmental organisation which
fosters social support. Use of self-reports may have possibly resulted in over-reporting of satisficing quality of
life. Low scores on the environmental domain seemed to be mainly due to lack of finances to lead a decent life,
lack of recreational activities in rural areas and transport costs to get medical attention. The fact that many
participants preferred the OI centre to their local treatment centres may suggest fear of stigma and
discrimination if their local community knew about their HIV positive status. However, there were constant
opportunities for up to date knowledge on HIV/AIDS and ART as each working day started with a well-
participated health education session conducted by OI clinic nurses. The high physical health despite low CD4
count may need further investigation.
The Cronbach’s alpha, internal consistency, for the individual domains ranged between 0.63 and 0.81.
The highest value was for domain 1, physical health and the least value was for domain 3, social relationships
which has only 3 items. The results are consistent with findings from previous studies (14;16)
. The instrument has
showed a resolute internal consistency over time. The overall reliability was excellent due to standardized
interviewing of participants.
The sociodemographic and clinical predictors of quality of life were responsible for between 0.19 and
0.31 of the changes in quality of life. Thus, being on ART alone does not guarantee quality of life. Many other
factors are responsible for the other 0.69 to 0.81 of the changes in quality of life. CD4 count is not significantly
related to quality of life, confirming findings in a recent Ugandan cohort (3)
and a Tanzanian study (6)
. In the
study, being male, a monthly income of more than US$250 and being on ART for more than 3 years was
associated with high quality of life. The findings tally with findings elsewhere (6;30;31)
. However, the income
needed for improvement in quality of life was quite low compared to the annual of above US$20 000 due to a
low cost of living in Masvingo, let alone in the rural areas. There is a need to increase income generating
projects targeted at people on ART to improve, not only environmental quality of life but also other quality of
life domains due to associated exercise, relaxation and mental preoccupation with productive activities. The
current study showed that it needs about 3 years on ART for quality of life to improve significantly, maybe due
to adjustment to side effects of antiretroviral drugs and psychosocial adjustment. However, a period of above 3
months on Art promises to be associated with improved quality of life, although the positive linear association
was not statistically significant. The promise may be due to the new Tenofovir®
-based ART regime which has
fewer side-effects, hence may lead to improved quality of life. If robust interventions are targeted at the

period,to improve knowledge, acceptance or stabilise uncomfortable side-effects, there may be considerable
improvements in quality of life. The positive relationship between Islam religion and the psychological well-
being domain of quality of life may have been due to the fact that all the Moslems in the sample were males.
Being male, in the study, was associated with a higher quality of life, though in the physical health and social
relations domains. Muslims constituted 1.7% of the sample. However, there is need for further investigation on
the Islam practices, diet, or attitudes which strengthens their psychological well-being.
The negative relationship between unemployment and quality of life is documented elsewhere (6;30;31)
.
This could explain the negative linear relationship, in the present study, between unemployment or being a
pensioner and quality of life. Moreover, a low income coupled with a raised cost of living in urban areas may
have negatively impacted on the quality of life for urban dwellers. A notable finding was the marital status of
being single. It was consistently associated with a low quality of life compared to cohabitation. It may be due to
the impact of HIV on future plans, for instance, child bearing and lack of an intimate partner for social support.
Cohabitation, with there being no strings attached may produce more happiness than other marital status.
Cohabitation may have other advantages such as presence of treatment buddies, financial and psychological
support. Traditional religion was associated with a reduction in quality of life, possibly due to concurrent use of
herbal medicine with ART. There is need to characterize quality of life in people who concurrently take herbal
medicine with antiretroviral therapy.
V. Conclusion
Quality of life is quite high on the physical health, psychological well-being domains and low on the
environmental domain. There was a positive linear relationship between being a male, having been on ART for
more than 3 years, a monthly salary US$251 and above and being a Moslem. On the other hand, quality of life
was negatively associated with being single, urban dwellers, unemployed, pensioners and traditionalists.
Vigilant interventions need to be done for urban dwellers, single individuals, pensioners, unemployed people
and traditionalists on ART to improve their quality of life. Income generating projects targeted at people on
ART may improve their quality of life. Quality of life cannot be extrapolated from the patient’s CD4 count
dynamics, but should rather be determined as a separate intervention. The WHOQOL BREF instrument is a
brief and reliable tool for monitoring quality of life of individuals on ART. There is need to examine why
physical health quality of life may remain high while the CD4 count is low implying a high risk of opportunistic
infections. Finally, being on ART alone does not improve quality of life. It is responsible for less than a third of
changes in quality of life.
Acknowledgements
The authors would like to acknowledge the WHO for permission to use the WHOQOL BREF instrument.
Reference List
[1]. Joint United Nations Programme on HIV/AIDS. How AIDS changed everything. 2015. UNAIDS, Geneva.Ref Type: Generic
[2]. Patterson S, Cescon A, Samji H, Chan K, Zhang W, Raboud J, et al. Life expectancy of HIV-positive individuals on combination
antiretroviral therapy in Canada. BMC Infect Dis 2015;15:274.
[3]. Mwesigire DM, Martin F, Seeley J, Katamba A. Relationship between CD4 count and quality of life over time among HIV patients
in Uganda: a cohort study. Health Qual Life Outcomes 2015;13:144.
[4]. Feng MC, Feng JY, Yu CT, Chen LH, Yang PH, Shih CC, et al. Stress, needs, and quality of life of people living with human
immunodeficiency virus/AIDS in Taiwan. Kaohsiung J Med Sci 2015 Sep;31(9):485-92.
[5]. Maluccio JA, Palermo T, Kadiyala S, Rawat R. Improving Health-Related Quality of Life among People Living with HIV: Results
from an Impact Evaluation of a Food Assistance Program in Uganda. PLoS One 2015;10(8):e0135879.
[6]. Magafu MG, Moji K, Igumbor EU, Hashizume M, Mizota T, Komazawa O, et al. Usefulness of highly active antiretroviral therapy
on health-related quality of life of adult recipients in Tanzania. AIDS patient care and STDS 2009;23(7):563-70.
[7]. Arjun BY, Unnikrishnan B, Ramapuram JT, Thapar R, Mithra P, Kumar N, et al. Factors Influencing Quality of Life among People
Living with HIV in Coastal South India. J Int Assoc Provid AIDS Care 2015 Aug 6.
[8]. Mutabazi-Mwesigire D, Katamba A, Martin F, Seeley J, Wu AW. Factors That Affect Quality of Life among People Living with
HIV Attending an Urban Clinic in Uganda: A Cohort Study. PLoS One 2015;10(6):e0126810.
[9]. Lifson AR, Grandits GA, Gardner EM, Wolff MJ, Pulik P, Williams I, et al. Quality of life assessment among HIV-positive persons
entering the INSIGHT Strategic Timing of AntiRetroviral Treatment (START) trial. HIV Med 2015 Apr;16 Suppl 1:88-96.
[10]. World Health Organization. Antiretroviral therapy for HIV infection in adults and adolescentsrecommendations for a public health
approach - 2010 revision. 2010 rev ed. Geneva: World Health Organization; 2010.
[11]. Plazy M, Dabis F, Naidu K, Orne-Gliemann J, Barnighausen T, Dray-Spira R. Change of treatment guidelines and evolution of
ART initiation in rural South Africa: data of a large HIV care and treatment programme. BMC Infect Dis 2015;15:452.
[12]. Lima VD, Reuter A, Harrigan PR, Lourenco L, Chau W, Hull M, et al. Initiation of antiretroviral therapy at high CD4+ cell counts
is associated with positive treatment outcomes. AIDS 2015 Sep 10;29(14):1871-82.
[13]. Suligoi B, Zucchetto A, Grande E, Camoni L, Dal ML, Frova L, et al. Risk factors for early mortality after AIDS in the cART era:
A population-based cohort study in Italy. BMC Infect Dis 2015;15:229.
[14]. Vosvick M, Koopman C, Gore-Felton C, Thoresen C, Krumboltz J, Spiegel D. Relationship of functional quality of life to strategies
for coping with the stress of living with HIV/AIDS. Psychosomatics 2003;44(1):51-8.
[15]. Taylor TN, Dolezal C, Tross S, Holmes WC. Comparison of HIV/AIDS-specific quality of life change in Zimbabwean patients at
western medicine versus traditional African medicine care sites. J Acquir Immune Defic Syndr 2008 Dec 15;49(5):552-6.

[16]. Xiaoyan X, Sato MK. Quality of life and related factors among people living with HIV in China. Journal of Nursing and Healthcare
of Chronic Illness 2011;3(4):513-20.
[17]. Pereira M, Canavarro MC. Gender and age differences in quality of life and the impact of psychopathological symptoms among
HIV-infected patients. AIDS and Behavior 2011;15(8):1857-69.
[18]. Nirmal B, Divya KR, Dorairaj VS, Venkateswaran K. Quality of life in HIV/AIDS patients: A cross-sectional study in south India.
Indian Journal of Sexually transmitted diseases and AIDS 2008;29(1):15.
[19]. World Health Organization. Antiretroviral therapy of HIV infection in infants and children: towards universal access:
recommendations for a public health approach-2010 revision. World Health Organization; 2010.
[20]. Skevington SM, Lotfy M, O'Connell KA. The World Health Organization's WHOQOL-BREF quality of life assessment:
psychometric properties and results of the international field trial. A report from the WHOQOL group. Quality of life Research
2004;13(2):299-310.
[21]. Hsiung PC, Fang CT, Chang YY, Chen MY, Wang JD. Comparison of WHOQOL-bREF and SF-36 in patients with HIV infection.
Qual Life Res 2005 Feb;14(1):141-50.
[22]. Hou WL, Chen CE, Liu HY, Lai YY, Lee HC, Lee NY, et al. Mediating effects of social support on depression and quality of life
among patients with HIV infection in Taiwan. AIDS Care 2014;26(8):996-1003.
[23]. Handajani YS, Djoerban Z, Irawan H. Quality of life people living with HIV/AIDS: outpatient in Kramat 128 Hospital Jakarta. Acta
Med Indones 2012 Oct;44(4):310-6.
[24]. Li Y, Baron J. Statistical Power and Sample Size Considerations. Behavioral Research Data Analysis with R. Springer; 2012. p.
129-37.
[25]. Zimbabwe National Statistics Agency (ZIMSTAT), ICF International. Zimbabwe Demographic and Health Survey 2010-1.
Calverton, Maryland: ZIMSTAT and ICF International Inc.; 2012.
[26]. ZIMSTAT (Zimbabwe National Statistics Agency). Zimbabwe Population Census 2012. Harare: Population Census Office; 2013.
[27]. Dowd AJ, Friedlander E, Guajardo J, Mann N, Pisani L. Literacy Boost Cross Country Analysis Results. 2013.
[28]. CHEN WEIT, SHIU CS, SIMONI JANE, ZHAO HONG. Complementary and alternative medicine and traditional Chinese
medicine in a Chinese population who are HIV positive: Perceptions and beliefs. HIV in Communities of Color 2011.
[29]. Van Damme W, Kober K, Kegels G. Scaling-up antiretroviral treatment in Southern African countries with human resource
shortage: how will health systems adapt? Social science & medicine 2008;66(10):2108-21.
[30]. Xiaoyan X, Sato MK. Quality of life and related factors among people living with HIV in China. Journal of Nursing and Healthcare
of Chronic Illness 2011;3(4):513-20.
[31]. Pereira M, Canavarro MC. Gender and age differences in quality of life and the impact of psychopathological symptoms among
HIV-infected patients. AIDS and Behavior 2011;15(8):1857-69.

Quality of life and its sociodemographic and clinicalpredictorsamong people on antiretroviral therapy (ART) at a resource-limited clinic.

More Related Content

What's hot (20)

Viewers also liked (20)

Similar to Quality of life and its sociodemographic and clinicalpredictorsamong people on antiretroviral therapy (ART) at a resource-limited clinic. (20)

More from iosrjce (20)

Recently uploaded (20)

Quality of life and its sociodemographic and clinicalpredictorsamong people on antiretroviral therapy (ART) at a resource-limited clinic.