Abstract

 

Adherence to antiretroviral medicines is essential to halt human immunodeficiency virus progression, increase CD4 counts, decrease virologic impact, and improve quality of life for the infected people. However, sustaining good adherence among adolescents and young adults (AYA) has been a challenge caused by various problems such as distance to clinic, improved CD4 count which lead to complacency in adherence, and the nature of the environment. This was a quantitative, retrospective, correlational, cross-sectional study anchored by the transtheoretical model, which was used to understand how adherence rate among the study population was impacted by the predictive factors.

Secondary data was collected from patient’s medical records at the Federal Medical Center, Owerri in Imo State, Nigeria. Univariate analysis was conducted using descriptive statistics. The study sample size of 656 patients was drawn from AYA ages 15–24 years. Independent t tests showed a statistically significant difference in adherence rates between rural (94%) and urban (89%) AYA, t (424) = -3.280, p = 001. There was also a statistically significant difference in adherence rates of ART for patients who lived within 50 kilometers of the hospital and those who lived more than 50 kilometers away from the hospital, t (509) = -2.37, p = .018. Also, there was a statistically significant correlation between adherence rate to ART and CD4 of less than 500 cells/mm³, R =

.214, p = .003. This study provides findings for HIV implementing partners (IPs) and relevant health professionals in Nigeria useful for designing strategies that would improve adherence rate to antiretroviral therapy among AYA in Nigeria.

 

 

Adherence to Antiretroviral Medicines among Adolescents and Young Adults in Imo State, Nigeria

 

Chapter One

Introduction

 

1.1 Background of the Study

 

According to the World Development Indicator, in 2013, per capital GDP in Nigeria was only $2,980, ranking it 131^st in the world (Ajakaiye, Jerome, Nabena, & Alabi A. Olufunke, 2015). The country is categorized as among the low- and medium- income countries. The first diagnosis of HIV in Nigeria was in Lagos in 1986. The following years saw numbers jump dramatically with two reported cases in 1987, 33 in 1988, and 9715 in the year 2000. At the onset of HIV in the country, there was a lot of skepticism about whether the disease was real or a mere ploy by the Western world to discourage sex and limit the perceived growth of African populations (Zeleza & Kakoma, 2003). Such skeptics even dubbed the acronym as “American idea of discouraging sex” (AIDS). Before the first sentinel survey in Nigeria, the prevalence of HIV was on a

 

steady rise. It was 1.8% in 1991, 3.8% in 1993, 5.4% in 1999, and 5.8% in 2001 (National Agency for the Control of AIDS (NACA), 2015). In 2011, with an estimated population of 180 million people, Nigeria had HIV prevalence rate of 3.3% (Bashorun et al., 2014). In 2015, the country had a projected population of 185 million (49% female and 51% male) with a recorded HIV prevalence rate of 3.1% (PEPFAR, 2016). The 2012 National HIV/AIDS and Reproductive Health Survey (NARHS), which was a more comprehensive survey compare to the ante-natal clinic (ANC) sentinel survey, reported the prevalence of HIV at 3.4% (National Agency for the Control of AIDS (NACA), 2015).

There are six geo-political zones in Nigeria: South South, South East, South West, North East, North West, and North Central (The Federal Republic of Nigeria, 1999). The distribution of HIV prevalence in Nigeria is not homogenous among the six geo-political zones. Initially, the southern axes had a comparatively higher rate; but over the years, the Middle Belt region of the country, made up of parts of North East, and North Central, has taken over (Bashorun et al., 2014). In 2012, South South, had the highest prevalence of 5.5%, while South East had the lowest prevalence of 1.8%.

 

 

 

 

Figure 1. HIV prevalence by geopolitical axes including national rates.

 

Compared to the national prevalence of 3.0% in 2012, only South West and South East (with prevalence of 2.8% and 1.8%, respectively) had less than the national prevalence as displayed in Figure 1 (National Agency for the Control of AIDS (NACA), 2015). In 2012, four states shown in Figure 2 had a prevalence greater than 8%, including Rivers (15.2%), Taraba (10.5%), Kaduna (9.2%), and Nasarawa (8.1%) respectively (National Agency for the Control of AIDS (NACA), 2015).

 

There is a disparity in prevalence between urban and rural settlement with the former having a higher prevalence of HIV (Mahy et al., 2014). Also, the prevalence was higher among female than male with 4.0% and 3.2% respectively in 2007. Five years later (2012), the female rate declined to 3.5% but was still higher than the male rate of 3.3% (National Agency for the Control of AIDS (NACA), 2015).  The age group 35 – 39 years had the highest prevalence in 2012 with 4.4% compared to age 15 – 24 which accounts for 42% of new infections globally (Kharsany & Karim, 2016; Wang et al., 2016).

 

The incidence of HIV peaked in 2009 with 278,061 new infections, and the rate of new infections has continued to decline with 262,238 in 2011, 239,155 in 2013 and 227, 518 in 2014 (National Agency for the Control of AIDS (NACA), 2015). Table 1 shows the trend of HIV incidence in Nigeria between 2009 and 2014. In 2015, Nigeria was responsible for over 30% of new infection among children globally (President’s Emergency Plan for AIDS Relief [PEPFAR], 2016).

The total number of deaths from HIV in Nigeria is unknown because there was no proper data documentation at the initial stage of HIV outbreak in the country. However, available data showed that mortality rate dropped from over 210,0000 in 2013 to slightly above 174, 000 in 2014 (President’s Emergency Plan for AIDS Relief [PEPFAR], 2016). The figure from the agency officially mandated by the federal government of Nigeria to

 

control HIV in the country, the NACA, estimated that 180,000 deaths in 2015 resulted from HIV-related causes (National Agency for the Control of AIDS (NACA), 2015). However, on the African continent to which Nigeria belongs, an estimated 790,000 people died of HIV-related causes in 2014, and this was less than the 1.2 million in 2009 and 1.5 million in 2004 (Granich et al., 2015). Maternal death related to HIV is fast emerging as the leading cause of pregnancy-related mortality (Onakewhor et al., 2011). HIV is one of the five preventable diseases that account for more than 70% of the leading causes of 1 million annual deaths of children under 5 in the world, annually. The other diseases are malaria, diarrhea, measles, and pneumonia (NACA, 2015). The number of children orphaned by HIV was estimated to be 1.7 million in 2013 (PEPFAR, 2016).

HIV transmission routes vary widely in different regions of the world. In Eastern Europe, South America, and Central Asia, the predominant routes are sex, drug, and men having sex with men (Shaw & Hunter, 2012). In Nigeria, researchers have conducted many studies on the transmission of HIV in Nigeria over the last two decades. The converging point for researchers on this seems that the primary means of HIV transmission in Nigeria remains men who have sex with men (MSM), use of intravenous drug, sexual contact with commercial sex workers (The Joint United Nations Programme on HIV and AIDS UNAIDS, 2010). Others means include through, blood transfusion, blood products, and maternal-infant infection (Shubber, Mishra, Vesga, & Boily, 2014; UNAIDS, 2010). Among the most at-risk populations, there has been a shift in prevalence. The group includes female sex workers, men who have sex with men (MSM),

 

long journey travelers, and IDUs (NACA, 2015). There is a prevalence of 27.4% among brothel-based female sex workers, 21.7% among non-brothel-based female sex workers, and 17.2% for MSM (National Agency for the Control of AIDS (NACA), 2015). Two decades ago, sex workers were thought to have the highest prevalence of HIV, but that is fast changing as the prevalence for MSM was 13.5% in 2007, but rose to 23% in 2015 (Entonu & Agwale, 2007).

1.2 Problem Statement

 

Adherence is a term used to describe the extent to which a patient’s behavior relating to medical treatment aligns with what was collectively agreed to between the patient and prescriber (Bello, 2011). Poor adherence to ART has been associated with failure of therapy, whereas good adherence is essential for the desired treatment outcomes such as improved quality of life and survival (Akahara, Nwolisa, Odinaka, & Okolo, 2017). For most of the countries where HIV is endemic like Nigeria, refill of ARVARVs at treatment centers is based on appointment (Mori & Owenya, 2014).

Patients are thus expected to also adhere to their clinic dates soas to have their prescriptions refilled. The ARV medicines are free of charge in Nigeria and other sub- Saharan Africa with support from the U.S. government and other foreign agencies (OGAC, 2014). The problem, however, is that HIV patients rarely attained a 100% rate in their pharmacy ARV refill. Pharmacy ARV refill is a proxy measure of adherence to ART (Sangeda et al., 2014a, 2014b). There have been reported challenges that inhibit adherence as enumerated earlier on such as transportation cost, forgetfulness, side effects associated with the ARVs and stigma (Arnet, Walter, & Hersberger, 2013; Groh et al., 2011; Hatah, Lim, Ali, Mohamed Shah, & Islahudin, 2015). The life-saving significance of the ARV medicines notwithstanding, adherence has been a challenge among AYA (Ankrah et al., 2016).

 

Globally, while 83% of adolescents living with HIV are in sub-Saharan Africa, their ART outcomes are poor when compared to adults (Ankrah et al., 2016; Maskew et al., 2016). Also, once on ARV, one is expected to be adherent to obtain and maintain good health outcomes (Heestermans, Browne, Aitken, Vervoort, & Klipstein-Grobusch, 2016). However, poor adherence has been reported among people with prior good adherence (Ngarina, Popenoe, Kilewo, Biberfeld, & Ekstrom, 2013). Some of the inhibitors to adherence among this population include financial barriers, adverse side effects of the ARV, forgetfulness, and stigma (Gare et al., 2015; Shigdel et al., 2014).

Thus far, there have been no studies in developing nations comparing rural and urban settings’ impact on adherence. A study in Uganda indicated that rural health facilities were associated with poor adherence measured by hospital prescription refill for patients who reside and access care in such rural areas (Nabukeera-Barungi et al., 2015). There is therefore a need to explore such association for patients who live in the rural area but access their care in faraway urban settings. Also, distance to the treatment center as reported by patients has been cited as an inhibitor of adherence (Conley et al., 2012).

However, no known study has explored this further using patient hospital records to correlate such claims.

1.3 Purpose of the Study

 

The purpose of the research was to explore the difference in adherence rate to ART in patients who resided in a rural setting and those who resided in urban settings. Because patients have reported distance as a barrier, I also stratified the population by distance to the treatment center and explored for correlation with adherence. In addition, I

 

explored relationship between a high CD4 count and adherence. Therefore, the specific goals of the quantitative study were (a) to explore the difference in adherence among adolescents and young adults (AYA) accessing care in the same treatment center but resident in rural and urban settings, (b) to explore the association between adherence in AYA stratified by distance from treatment center, (c) to determine the nature of the relationship between adherence and CD4 counts after an adolescent or young adult attained a good CD4 cell count greater than 500 cell/ mm³.

1.4 Research Questions

 

I developed the following three research questions (RQs) for this study:

 

RQ1: What is the difference in adherence to ART among AYA accessing ARV medicines in the same treatment center but residing in rural and urban settings?

Ho1: There is no statistically significant difference in adherence to ART among AYA accessing ARV medicines in the same treatment center but residing in rural and urban settings

Ha1: There is statistically significant difference in adherence to ART among AYA accessing ARV medicines in the same treatment center but residing in rural and urban settings

RQ2: What is the association between distance from treatment center and adherence to ART among AYA?

Ho2: There is no statistically significant association between distance from treatment center and adherence to ART among AYA

 

Ha2: There is statistically significant association between distance from treatment center and adherence to ART among AYA.

RQ3: What is the relationship between a high CD4 counts (> 500 cell/mm³) and adherence to ART among AYA?

Ho3: There is no statistically significant relationship between a high CD4 counts (> 500 cell/mm³) and adherence to ART among AYA.

Ha3: There is statistically significant relationship between a high CD4 counts (> 500 cell/mm³) and adherence to ART among AYA.

1.5 Definitions of Study Variables and other Terms

 

Acquired immune deficiency syndrome (AIDS): A collection of symptoms that is best described as a syndrome caused by HIV (Sharp & Hahn, 2011).

Adherence: A term used in describing the extent to which a patient’s behavior relating to medical treatment agrees with what was collectively agreed with the prescriber (Bello S.I, 2011).

Adolescent: A person between 10 and 18 years old. Defining adolescent strictly from the perspective of age has been criticized by many. A complete definition of an adolescent should consider the biopsychosocial stage of a young person entering an adult stage of life (Curtis, 2015).

CD4 count: A test that measures the number of CD4 cells in the body. These CD4 cells, also called T cells, are the type of white cells that defend the body against infection.

 

It does not measure HIV but is a surrogate HIV marker that indicates not just presence of HIV but how much damage it has caused to the body. CD4 count serves as an indicator of body immunity (Nwokedi, Ochicha, Mohammed, & Saddiq, 2007).

Distance to treatment center: This refers to the distance between the ART center and where the participant resides.

Geopolitical zone: Refers to the zones in Nigeria based on geographical location and political consideration. Economic, political, and educational resources often are shared across the zones (Ibrahim & Ibrahim, 2014).

HIV treatment center: This is a designated health facility for management of HIV/AIDS.

Human immunodeficiency virus (HIV): The virus that spreads through bodily fluids and causes AIDS, a life-threatening disease, by attacking CD4 cells.

Mortality: Incidence of death with a particular group in a specified period.

 

Pharmacy refill: Prescription refill in pharmacy.

 

Rural: This refers to a hamlet or village settlement.

 

Self-disclosure: The act of revealing information about oneself to another person (Nöstlinger, Bakeera-Kitaka, Buyze, Loos, & Buvé, 2015).

Self-report: Report about a patient as presented by the patient.

 

Serodiscordance: A term use in reference to a couple that has “mixed serostatus.” That is one partner is HIV-positive while the other is HIV-negative (Irungu et al., 2016).

Urban: This refers to a town or city settlement.

 

Young adult: According to WHO, a young adult is a person aged 12–24 (Geiger & Castellino, 2011).

1.6 Scope and Delimitations

 

I explored the adherence rates of AYAs in Nigeria accessing ART between 2011 and 2014 to see how the group differs with respect to distance, CD4 counts and type of environemnt. Adherence is crucial for the successful management of HIV globally. AYA are the links between pediatric and adult, and as such, poor adherence to ARVs from this group could mean a serious public health issue given that one has to remain on these drugs for life. HIV is prone to becoming resistant to ARVs if the adherence component of HIV management is not handled carefully. Once there is resistance to any ARV, HIV infection becomes a public health challenge.

The study was restricted to data from AYA who are living with HIV/AIDS and are currently enrolled in ART in the FMC Owerri, Imo State, Nigeria. I used a retrospective, correlational, cross-sectional design for quantitative analysis (Gordis, 2009). This methodology is employed when a researcher wants to explore relationships between variables without establishing causation (Campbell & Stanley, 1963; C Frankfort-Nachmias & Nachmias, 2015; Mann, 2003). This study does not establish causality but shows association, so the methodology is appropriate because the focus of

 

my research was not to establish causality but to explore the nature of relationship between adherence rate and predictor variables—namely CD4 counts, distance from ART center and nature of settlement among adolescents and AYA. Also, the secondary data I used was collected at one particular point in time, which fulfills the requirements of a cross-sectional study. Another merit of the cross-sectional methodology is that it could be used for description of the odds ratio, absolute risks, and relative risk from prevalence (Thompson, Myers, & Kriebel, 1998).

1.7 Significance

 

ART adherence improves quality of life, reduces hospitalization with attendant cost implications, and reduces the incidence of HIV-related morbidity and mortality (Falang et al., 2012). Adherence at rates below 85% a serious public health issue because it potentially causes resistance to the currently limited available ARVregimens (Kadhiravan, 2013). For example, resistance to first-line ARVs means a patient would have only a second-line regimen and salvage regimen as the remaining options (Masikini & Mpondo, 2015). There is an attendant increased total health cost associated with poor adherence as well because health outcome is impacted negatively, thereby increasing the frequency of clinic visits, transportation costs, and pill burden with an additional cost implication. Non-adherence has been linked to treatment failure as well (Inzaule, Hamers, Kityo, Rinke De Wit, & Roura, 2016).

Two-thirds of new infections of HIV in 2012 were among AYA aged 15-24 years (Bekker, & Hosek, 2015). Between 2002 and 2012, AIDS-related mortality dropped by 30% for all age categories except AYA, whose rate increased by 50% for the same period (Bekker et al., 2015). The research is unique because despite many studies on factors that negatively influence adherence among AYA, researchers have not explored the effect of an environment such as urban or rural setting. Also, if the distance to a treatment center is stratified and there is no correlation with adherence, then findings from the research would shed knowledge on a need for a shift in the current adherence strategies.

 

Furthermore, identifying an adherence inhibitor would call for a counter strategy that would be in line with the ambitious treatment target of the UNAIDS to have viral suppression in 90% of people living with HIV globally (UNAIDS, 2014). For a HIV-free generation, viral suppression in 90% of the infected population is essential.