The research team, led by Geoffrey Mariga Mariita of Great Lakes University of Kisumu together with colleagues from the USAID DUMISHA Afya Project, interviewed 300 adult patients aged 18 years and older who were enrolled in antiretroviral therapy care at Level 4 and Level 5 public health facilities in Busia County. Rather than relying on convenience sampling, the investigators used probability-proportional-to-size sampling combined with systematic random selection, a design that gives larger facilities a proportionally greater chance of contributing participants and reduces the risk that a single clinic’s idiosyncrasies dominate the results. Structured interviews were conducted in Kiswahili and covered five domains: socio-demographic characteristics, cultural factors, psychosocial factors, health-service factors, and socio-economic factors.

A methodological strength of the study lies in its definition of the primary outcome. Adherence status was not self-reported, which is notoriously prone to social desirability bias, but instead derived from Electronic Medical Record pharmacy pick-up records. A patient was classified as non-adherent if a scheduled medication pick-up was missed by more than 28 days within the preceding six months. Viral load results and pill counts were abstracted as secondary corroborating indicators, allowing the researchers to triangulate their classification against clinical and behavioral measures. This objective anchor matters, because much of the adherence literature in sub-Saharan Africa rests on patient recall, which can overestimate adherence substantially.

The headline result is, on its face, encouraging. Of the 300 participants, 272, or 90.7 percent, were classified as adherent, while only 28, or 9.3 percent, fell into the non-adherent category. The cohort was 60 percent female and 40 percent male, a distribution consistent with the demographics of HIV care in much of eastern Africa. A non-adherence rate below ten percent, measured against a strict pharmacy-based definition, suggests that the treatment system in Busia County is reaching most patients effectively, even in a border region characterized by population movement, cross-border trade, and the logistical complications that mobility brings to chronic disease care.

Yet the study’s central analytical contribution lies in identifying which of the many candidate factors actually predicted non-adherence. The researchers first assessed bivariate associations using chi-square tests, then built a multivariable logistic regression model to estimate independent predictors, and finally cross-checked those estimates against a mixed-effects model that accounted for clustering of patients within facilities. This dual-model strategy is important: patients at the same hospital share providers, drug stock levels, and local norms, and ignoring that clustering can produce misleadingly narrow confidence intervals. Only two variables survived both modeling approaches.

The first was sex. Female participants had significantly lower odds of non-adherence than male participants, with a logistic regression odds ratio of 0.48 and a 95 percent confidence interval of 0.23 to 1.00, at a p-value of 0.049. The facility-clustered mixed-effects model confirmed the association, reporting a coefficient of negative 0.091 with a p-value of 0.035. In practical terms, men in this cohort were roughly twice as likely as women to miss a scheduled pharmacy pick-up by more than a month. This pattern echoes a broader and increasingly recognized phenomenon in global HIV care: men across sub-Saharan Africa are less likely to test for HIV, initiate treatment later, and disengage from care more often than women, partly because clinic services and outreach programs have historically been designed around antenatal and maternal health touchpoints that women encounter routinely.

The second independent predictor was educational attainment. Higher education was associated with lower odds of non-adherence, with an odds ratio of 0.56, a 95 percent confidence interval of 0.35 to 0.89, and a p-value of 0.015. The mixed-effects model again corroborated the finding, with a coefficient of 0.064 and a p-value of 0.012. The mechanism is plausibly multifaceted: education correlates with health literacy, the ability to navigate appointment systems, comprehension of dosing instructions, and economic stability, all of which can smooth the practical friction of lifelong daily medication. Whatever the precise pathway, the result implies that adherence support materials and counseling delivered at a single literacy level may leave the least-educated patients behind.

Equally notable is the list of factors that did not independently predict adherence. Marital status, social support, cultural beliefs, religious beliefs, stigma, patients’ ratings of health services, and difficulty balancing antiretroviral drugs with a prescribed diet all failed to reach statistical significance in either model. This null result is a caution against over-reading smaller studies: the authors themselves note that the most plausible explanation is limited statistical power, since only 28 patients were non-adherent, leaving a small subgroup in which even moderately sized effects are hard to detect. In other words, the absence of significance for stigma or social support should not be interpreted as evidence that these factors are irrelevant, but rather that this dataset cannot resolve their contribution. The finding nonetheless challenges the assumption, common in program design, that psychosocial and cultural variables are always the dominant drivers of adherence in rural African settings.

The context of Busia County sharpens the significance of these results. Kenya has made substantial national progress toward the UNAIDS 95-95-95 targets, which call for 95 percent of people living with HIV to know their status, 95 percent of those diagnosed to be on sustained treatment, and 95 percent of those on treatment to achieve viral suppression. National aggregates, however, can conceal pockets of vulnerability, and border counties with high population mobility are precisely the places where local evidence has been thinnest. By grounding adherence measurement in pharmacy records across multiple public facilities, including Busia County Referral Hospital, Khunyangu Sub-County Hospital, Port Victoria Hospital, and Teso North Sub-County Hospital, the study provides the kind of locally actionable data that national dashboards cannot supply.

The authors’ recommendations follow directly from their two robust findings. They call for sex-responsive adherence support, meaning interventions deliberately designed to reach and retain men, who emerge from this cohort as the higher-risk group, and for literacy-appropriate counseling and materials that meet patients across the full educational spectrum. They also urge adequately powered follow-up research, ideally with larger samples or longitudinal designs, to clarify whether the commonly cited barriers that fell out of significance in Busia, such as stigma and social support, exert real effects that this study was underpowered to detect. Ethical oversight was thorough, with approval from the Great Lakes University of Kisumu Scientific and Ethical Review Committee and the National Commission for Science, Technology and Innovation, and written informed consent from all participants. The study received no dedicated funding, and the authors declare no competing interests. As antiretroviral therapy programs worldwide pivot from simply getting patients onto treatment to keeping them virally suppressed for decades, evidence of this granularity, drawn from the borderlands where health systems are tested hardest, will be essential for targeting the last stubborn gaps in the HIV response.

Subject of Research: Determinants of adherence to antiretroviral therapy among HIV patients in Busia County, Kenya

Article Title: Determinants of adherence to antiretroviral therapy among patients in Busia, Kenya

Article References: Mariita, G. M., Ashiono, E., Florence, T. Z., Charles, W., Kimuli, D., & Nyanchoka, V. (2026). Determinants of adherence to antiretroviral therapy among patients in Busia, Kenya. BMC Health Services Research. https://doi.org/10.1186/s12913-026-15739-w

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15739-w

Keywords: antiretroviral therapy, HIV, adherence, Kenya, Busia County, viral suppression, pharmacy refill records, health services research, sex differences, educational attainment, UNAIDS 95-95-95, cross-sectional study