Abstract
Introduction
HIV testing is vital for early detection and treatment linkage, yet uptake among children remains a global challenge. The 2016 Ethiopian Demographic and Health Survey (EDHS) revealed low HIV testing prevalence in children under 15 years old, with significant urban-rural disparities. This study analyzes these disparities and their contributing factors using EDHS data.
Methods
A cross-sectional analysis of the 2016 EDHS was conducted using STATA version 17.0. Chi -square tests were used to assess the associations between HIV testing uptake and independent variables, while multivariate decomposition analysis was used to analyze the factors associated with the urban–rural disparities of pediatric HIV testing uptake. Statistical significance was declared, at p-values < 0.05, with 95% confidence intervals reported. The results were presented using text, tables, and figures.
Results
The overall prevalence of pediatric HIV testing uptake was 18.61% (95% CI: 18.15%–19.07%), with significantly higher uptake in urban areas (35.66%) compared to rural areas (14.91%) (p < 0.001). A multivariate decomposition analysis revealed a substantial urban–rural disparity (0.21, p < 0.001), of which 50.34% was explained by differences in population characteristics, while 49.66% was due to differences in the effects of these characteristics. Key contributors to the disparity included household wealth, maternal education, child age, family size, premarital HIV testing, and consent refusal.
Conclusion and Recommendation
This study revealed a significant urban–rural disparity in pediatric HIV testing uptake, largely explained by differences in population characteristics. Thus, family size and parental education, were found to contribute to increased disparities. Conversely, premarital HIV testing, refusal of consent, and older maternal age demonstrated effects that influenced and, in some cases, reduced the observed gap. The findings suggest the need for targeted, equity-focused interventions to reduce urban-rural disparities in pediatric HIV testing.
Keywords: Ethiopia, HIV testing uptake, pediatrics, urban-rural disparities
Plain Language Summary
HIV testing helps detect infection early and ensures children receive timely treatment. However, many children in Ethiopia are not tested, especially those living in rural areas. This study used national survey data (EDHS 2016) to understand why these differences exist. The findings showed that children in urban areas were much more likely to be tested for HIV than children in rural areas. About half of this gap was due to differences in characteristics such as family wealth, maternal education, family size, and child age. The other half was related to how these factors influence testing differently across settings. The study also found that some factors, such as premarital HIV testing and consent-related issues, play a role in shaping testing patterns. These results suggest that improving access to HIV testing in rural areas, increasing health education, and supporting disadvantaged families could help reduce this gap and ensure more children receive HIV testing services.
Introduction
The Human Immunodeficiency Virus epidemic remains a global burden, particularly in Sub-Saharan Africa and Ethiopia, where the disease disproportionately affects children under 15 years. 1 In 2023, Joint United Nations Programme on HIV/AIDS (UNAIDS) reported approximately 1.4 million children (0–14 years) living with HIV of whom about 130,000 were newly infected.2,3 HIV testing is crucial for early identification of infections, initiation of antiretroviral therapy (ART), and prevention services. 4 However, testing uptake among children remains a critical challenge. Globally, only about 57% of children living with HIV (CLHIV) are receiving ART, indicating a significant gap in diagnosis and treatment coverage. 5
In Ethiopia, undiagnosed pediatric HIV remains a persistent challenge. Evidences showed that, only about two-thirds of HIV-exposed infants are diagnosed early. 6 The Ethiopian Ministry of Health (EMOH) targets 95-95-95 goals by 2030 (95% diagnosed, on treatment, and virally suppressed and mother-to-child transmission less than 2%. 7 To achieve this, EMOH has decentralized free ART to public and private facilities, scaled index testing, and launched community campaigns over two decades. Yet pediatric HIV testing gaps persist. The 2020 Ethiopian Population-based HIV Impact Assessment (EPHIA) shows that only about 40% of Ethiopia’s estimated 44,000 CLHIV receive ART. This highlights persistent pediatric case-finding gap. 8 The 2016 Ethiopian Demographic and Health Survey (EDHS) reported marked urban-rural disparities in pediatric HIV testing, with a substantially higher rate in urban areas (21.6%) than in rural areas (4.6%). This disparity highlights a critical gaps in healthcare access and service utilization. 9
Evidences showed that access to health facilities, exposure to health information, household income, parental education, stigma, discriminatory altitude and parent-to-child transmission were factors delay testing of HIV-exposed and symptomatic children.3,5,10-12 Previous studies have also shown that vertically infected children often remain undiagnosed due to caregiver-related stigma, socioeconomic disadvantages, and limited awareness of pediatric HIV13-15. Furthermore, one study reported that only 40.3% of rural men had ever been tested for HIV, suggesting that similar disparities may exist among pediatric populations. 10
To our knowledge, no previous study in Ethiopia has specifically examined urban-rural disparities in pediatric HIV testing uptake. Existing evidence has largely focused on adults and does not adequately address children. Multivariate decomposition analysis provides a robust approach to address urban -rural disparities by quantifying the relative contribution of each factor to the observed disparity. Unlike previous Ethiopian studies that focused primarily on determinants of HIV testing, this study quantifies the contribution of socioeconomic and demographic factors to urban-rural disparities in pediatric HIV testing uptake using nationally representative EDHS 2016 data, thereby providing evidence to inform targeted, equity-focused interventions.
Methods
Study Design and Data Source
This study used data from the 2016 EDHS, which is the most recent nationally representative dataset containing detailed information on pediatric HIV testing and relevant socioeconomic variables in Ethiopia. The EDHS was conducted by the Ethiopian Statistical Service (ESS) in collaboration with ICF. The EDHS is a cross-sectional survey that collects data on various health and demographic indicators. It uses standardized and internationally validated questionnaires developed by the DHS Program. These instruments are pre-tested, translated into local languages, and administered by trained interviewers to ensure reliability and comparability across settings. Data collection for the 2016 EDHS was conducted from January 18 to June 27, 2016. The dataset was accessed from the DHS Program website (https://dhsprogram.com/data/) after registration and approval. As the data are anonymized and publicly available, no additional ethical approval was required for this secondary analysis. The authors were not involved in the sampling design or data collection.
Sample Size and Sampling Design
The study population consisted of children under 15 years from the 2016 EDHS, totaling 27,713 individuals across Ethiopia’s 9 regions and 2 city administrations, stratified into 21 urban/rural domains. The sampling frame derived from the 2007 Population and Housing Census listed 84,915 enumeration areas (EAs) (details in 2016 EDHS report). A nationally representative sample was obtained via two-stage stratified sampling: in first stage, 645 EAs (202 urban, 443 rural) were selected with probability proportional to size within each of the 21 strata, using implicit stratification by ordering EAs according to major administrative units; in second stage, a fixed number of households underwent systematic selection from fresh EA.9,16
Inclusion and Exclusion Criteria and Sample Selection
This study included all children aged 0–14 years in the 2016 EDHS dataset. Children were included if complete information was available on HIV testing status and significantly associated variables. Observations with missing or incomplete data were excluded. The final sample consisted of 27,713 children after applying inclusion and exclusion criteria.
Measurements and Operational Definitions
Dependent variable: The outcome variable was pediatric HIV testing uptake, defined as whether a child under 15 years of age (0-14 years) had ever been tested for HIV. This information was obtained from the child’s mother or primary caregiver during the EDHS household interview and is based on caregiver self-report. The measure reflects whether the child had ever been tested for HIV at any time prior to the survey and not within a specific time period. The variable was coded as a binary outcome (1= Yes, the child has ever been tested; 0= No, the child has never been tested).
Stratifying variables: Place of residence was used as the main stratifying variable to assess differences in pediatric HIV testing uptake across population groups. In the EDHS dataset, residence is categorized as either urban or rural based on established administrative and geographic classifications. It was coded as a binary indicator (0 = urban, 1 = rural) and applied in the decomposition analysis to evaluate disparities between these groups.
Independent Variables: Based on their availability in EDHS data sets and the previous literature, the following variables were chosen as independent variables for this study: age of child (< 1 year, 1-4year, 5-14 year), maternal age (15-19, 20-24, 25-29, 30-34, 35-39, 40-44, 45-49), marital status (married, widowed, divorced, separated, never in union), education(no education, primary, secondary, higher), occupation(not working, professional, agricultural, trade, elementary work, others), religion (Orthodox, Muslim, Protestant, Catholic, Others), number of living children (≤ 4, > 5). Consent for HIV testing (granted, refused, lost) refers to whether the caregiver provided permission for HIV testing of the child. It was categorized as “granted” (consent given), “refused” (consent denied), and “don’t know/missing” (previously labeled as “lost). Premarital HIV testing refers to whether the mother had ever undergone HIV testing before marriage (Yes/No). HIV knowledge was assessed using eight standard DHS questions. Respondents who correctly answered six or more items were classified as having adequate knowledge, while those who answered fewer than six correctly were classified as having inadequate knowledge, 1 and wealth status (poor, medium, rich). This was measured using the wealth index, which is a composite measure of household assets and living conditions. The poor wealth index category was created by combining poorer and poorest, and the rich wealth index category was created by combining richer and richest. Community-level factors recorded were the place of residence (“rural” or “urban”) and geographical region (Oromia, Amhara, Tigray, Southern Nations, Nationalities, and Peoples’ Region (SNNPR), Somalia, Afar, Benishangul, Gambela, Addis Adaba, Harari, Dire dawa). Stigma and discriminatory attitudes toward HIV: It was derived from two DHS questions 1 : willingness to buy vegetables from an HIV-positive vendor, and 2 whether HIV-positive children should be allowed to attend school with HIV-negative children. Respondents answering “yes” to both were categorized as having “no stigma/discriminatory attitude coded as “0”, while those answering “no” or “don’t know” to one or both items were classified as having “stigma/discriminatory attitudes coded as “1”.2,8-11
Data Processing and Analysis
Data analysis was conducted using STATA version 17.0 to account for the complex survey design of the EDHS, sampling weights (v005/1,000,000) were applied, and the survey (svyset) command was used to adjust for clustering and stratification, ensuring nationally representative estimates and correct standard errors. 17
Descriptive statistics were computed to summarize the sociodemographic characteristics of the study population, and the results were presented as weighted frequencies and percentages. The association between pediatric HIV testing uptake and independent variables was initially assessed using Pearson’s chi-square test. After identification of significant predictors based on availability in data set and pervious literature, a multivariate decomposition analysis based on a logit model was conducted to examine urban rural disparities in pediatric HIV testing uptake.16,18 The mvdcmp command in STATA was used to decompose the observed difference in testing uptake between rural and urban populations into two components 1 : differences in population characteristics (endowments) and 2 differences in the effects of these characteristics (coefficients). This approach allows for quantifying the relative contribution of each factor to the observed disparity.
Reporting Guideline
This study complies with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. 19 The completed STROBE checklist has been provided as a supplementary file (Supplementary File 1).
Results
Descriptive Analysis
The overall weighted prevalence of pediatric HIV testing uptake was 18.61% (95% CI: 18.15%–19.07%). Uptake was significantly higher in urban areas (35.66%) compared to rural areas (14.91%). Conversely, a higher proportion of rural children (85.09%) had never been tested compared to urban children (64.34%). Of the participants, about 85.92% were rural dwellers who had never been tested for HIV, and 14.08% were urban dweller who had never been tested for HIV. Regarding marital status, the majority of mothers (91.86%) were married. More than two-thirds of the mothers (71.07%) had no formal education. In terms of household wealth status, more than half of the participants (52.33%) were from poor households, while approximately one-third (33.21%) were from rich households (Table 1).
Table 1.
Descriptive Analysis of Independent Variables Associated With Pediatric HIV Testing Uptake in Urban and Rural Ethiopia, EDHS 2016
| Variables | Categories | HIV testing uptake | Residency | ||
|---|---|---|---|---|---|
| Yes (%) | No (%) | Urban (%) | Rural (%) | ||
| Places of residency | Urban | 1,761(35.66) | 3,177(64.34) | | |
| Rural | 3,396(14.91) | 19,379(85.09) | |||
| HIV testing uptake | Yes | | 1,761(34.15) | 3,396(65.85) | |
| No | 3,177(14.08) | 19,379(85.92) | |||
| Age of child | < 1 year | 557(13.74) | 3,497(86.26) | 839(20.70) | 3,215(79.30) |
| 1-4 year | 979(16.45) | 4,973(83.55) | 1,068(17.94) | 4,884(82.06) | |
| 5-14 year | 3,621(20.45) | 14,086(79.55) | 3,031(17.12) | 14,667(82.88) | |
| Mother’s age | 15-19 | 65(17.06) | 316(82.94) | 54(14.17) | 327(85.83) |
| 20-24 | 371(14.25) | 2,233(85.75) | 458(17.59) | 2,146(82.41) | |
| 25-29 | 1,021(16.53) | 5,156(83.47) | 1,212(19.62) | 4,965(80.38) | |
| 30-34 | 1,365(19.17) | 5,755(80.83) | 1,391(19.54) | 5,729(80.46) | |
| 35-39 | 1,087(17.55) | 5,107(82.45) | 1,072(17.31) | 5,122(82.69) | |
| 40-44 | 837(24.16) | 2,628(75.84) | 521(15.04) | 2,944(84.96) | |
| 45-49 | 411(23.19) | 1,361(76.81) | 230(12.98) | 1,542(87.82) | |
| Mother education | No education | 3,043(15.54) | 16,654(84.55) | 1,825(9.27) | 1787(90.73) |
| Primary | 1,402(23.62) | 4,533(76.38) | 1,598(26.93) | 4,337(73.07) | |
| Secondary | 445(32.53) | 923(64.55) | 905(6.15) | 436(33.85) | |
| Higher | 267(37.45) | 446(62.55) | 610(85.55) | 103(14.45) | |
| Respondent’s occupation | Not working | 300(10.12) | 2,664(89.88) | 420(14.17) | 2,544(85.83) |
| Professional | 288(16.45) | 1,463(83.55) | 762(43.52) | 989(56.48) | |
| Agricultural | 3,514(21.18) | 13,079(78.82) | 1,116(6.73) | 15,477(93.27) | |
| Trade | 266(14.98) | 1,510(85.02) | 805(45.33) | 971(54.67) | |
| work | 183(20.00) | 697(79.20) | 378(42.95) | 502(57.02) | |
| Others | 606(16.16) | 3,143(83,84) | 1,475(38.86) | 2,292(61.14) | |
| Region | Orthodox | 65(17.06) | 316(82.94) | 54(14.17) | 327(85.83) |
| Muslim | 1,365(19.17) | 5,755(80.83) | 1,391(19.54) | 5,729(80.46) | |
| Protestant | 1,021(16.53) | 5,156(83.47) | 1,212(19.62) | 4,965(80.38) | |
| Catholic | 371((14.25) | 2,233(85.75) | 458(17.59) | 2146(82.41) | |
| Other | 2,335(20.43) | 9.096(79.75) | 1,823(15.95) | 9,608(84.05) | |
| Region | Emerged | 1,500(14.61) | 8,765(85.39) | 1,496(14.57) | 8,769(85.43) |
| Developed | 3,657(20.96) | 13,791(79.04) | 3,442(19.73) | 14,006(80.27) | |
| Wealth | Poor | 2,049(14.13) | 12,454(85.87) | 480(2.81) | 14,095(97.19) |
| middle | 633(15.80) | 3,373(84.20) | 126(3.15) | 3,880(9685) | |
| Rich | 2,475(26.89) | 6,729(73.11) | 4404(47.85) | 4,800(52.15) | |
| Number of children <15 | ≤ 4 | 3,057(22.36) | 10,613(77.64) | 3,627(26.53) | 10,043(73.47) |
| ≥ 5 | 2,100(14.95) | 11,943(85.05) | 1311(9.34) | 12.732(90.66) | |
| Consent of HIV | Granted | 4,829(18.42) | 21,380(81.58) | 4,446(16.96) | 21,763(83.04) |
| Refused | 189(19.96) | 758(80.04) | 369(38.97) | 578(61.03) | |
| Loss | 139(24.96) | 418(75.04) | 123(22.08) | 434(77.92) | |
| Pre-marital HIV test | No | 4,093(17.42) | 19,408(82.58) | 3168(33.48) | 20.333(86.52) |
| Yes | 1,064(25.26) | 3,148(74.74) | 1,770(42.02) | 2,442(57.98) | |
| Knowledge | Adequate | 3,750(18.84) | 16,531(81.16) | 3,558(17.88) | 16,345(82.12) |
| Inadequate | 1,407(18.02) | 6,403(81.89) | 1,380(17.67) | 3,558(17.88) | |
| Stigma and discriminatory | No | 3,732(18.45) | 16,492(81.55) | 3,603(17.82) | 16,621(82.18) |
| Yes | 1,425(19.03) | 6,064(80.97) | 1,335(17.83) | 6,154(82.17) | |
| Health insurance coverage | No | 4,915(18.43) | 21,758(81.57) | 4,704(17.64) | 21,969(82.36) |
| Yes | 242(23.27) | 798(76.73) | 234(22.50) | 806(77.50) | |
The multivariate decomposition analysis of urban-rural HIV testing uptake shows a significant disparity. This disparity was decomposed into three components, namely, a gap due to the difference in the composition of characteristics (i.e., explanation/endowment), a difference in the effect of the characteristics (i.e., coefficient), and a gap due to the interaction between the two components. The overall decomposition result revealed that there is a significant disparity in pediatric HIV testing uptake between urban and rural settings (0.21, p<0.001). The study found that 50.34% (p<0.001) of the HIV testing uptake rate disparities were due to the differences in the distribution of characteristics (endowments (E)) of children between urban and rural, whereas the differences in the effects of characteristics account for 49.66% (p<0.001) of the observed disparity in pediatric HIV testing uptake.
The multivariate decomposition analysis of the contribution of individual characteristics in the HIV testing uptake rate disparity in rural urban setting among pediatrics due to difference characteristics and due to coefficient of characteristics (Table 2).
Table 2.
Multivariate Decomposition Analysis of Urban–Rural Disparities in Pediatric HIV Testing Uptake, Ethiopia (EDHS 2016)
| Decomposition component | Coefficient with 95% CI | Percent | p-value |
|---|---|---|---|
| Row difference | 0.21(0.19,0.22) | 100 | 0.000 |
| Explain | 0.104 (0.08, 0.129) | 50.34 | 0.000 |
| Un explain (U) | 0.103(0.07, 0.129) | 49.66 | 0.000 |
Key Note: *= p-value < 0.05, E: Component/Change in characteristics; C: Component/Change in coefficient; 1: Reference.
The wealth status disparity between urban and rural areas accounted for the majority of the pediatric’ HIV testing uptake disparities. One factor contributing to the disparity is the composition of rich wealth status (24.32%); it was found that the disparity in HIV testing uptake will be reduced by 24.32% when the rich wealth composition of children in rural and urban settings is equalized. In contrast, middle-class status components did not significantly contribute to the disparity.
Moreover, several compositional factors contributed significantly to the urban–rural disparity in pediatric HIV testing uptake. Household characteristics such as having five or more children (19.33%) and higher levels of maternal education, including primary (3.70%), secondary (8.27%), and higher education (8.60%), showed positive contributions, indicating that these factors increase the disparity between rural and urban populations. Similarly, paternal primary education (2.66%) also contributed positively to widening the observed gap.
In contrast, some factors had negative contributions, suggesting that they reduce the urban–rural disparity. These include maternal age in the 40–44 and 45–49 age groups (−1.74% and −1.83%, respectively), refusal of consent for HIV testing (−1.23%), and premarital HIV testing (−7.53%). These negative contributions indicate that differences in these characteristics between rural and urban populations help narrow the observed gap in pediatric HIV testing uptake.
Other variables, including most maternal age categories and health insurance coverage, did not show statistically significant contributions in the coefficient component.
Discussion
This study aimed to explore the urban-rural disparities in pediatric HIV testing uptake in Ethiopia using data from the EDHS 2016. In this study finding, a significant difference between urban and rural settings, with identifying sociodemographic factors contributing to this disparity such as wealth status, maternal education, age of mother, age of child, parental education, premarital test and refused consent.
The decomposition analysis indicated a significant rural-urban gap in pediatric HIV testing uptake (0.21, 95% CI: 0.19-0.22, p<0.001), with testing uptake substantially higher in urban areas. About 50.34% of the disparity was explained by differences in population characteristics (endowments), while 49.66% was attributable to differences in the effects of these characteristics across settings.
This suggests that both structural inequalities (e.g., unequal distribution of resources) and contextual differences in how these factors influence behavior contribute almost equally to the observed disparity. Similar findings have been reported in studies conducted in Ethiopia and other settings.10,20 The possible reason might be that rural populations had low HIV testing due to low health care services, distance and transportation, concentration of facilities in urban areas, shortages of HIV test kits, and lower media exposure.21,22 These findings highlight that addressing urban–rural disparities requires both distributional strategies and interventions targeting behavioral and health system factors. For example, Ethiopian has implemented initiatives like the HIV/AIDS National Strategic Plan (2021-2025), which emphasizes expanding index testing, community-based self-testing, and rural outreach to achieve the goal regardless of urban-rural residence. 7 This study found that wealth status was a primary driver, accounting 24.32% of the difference when comparing rich wealth status between urban and rural children. This indicates that unequal distribution of socioeconomic resources is a key driver of inequality in pediatric HIV testing uptake. The finding is aligned with previous studies.10,20,23,24 The possible explanation is wealthier households are more likely to live closer to healthcare facilities, have better transportation options, and access resources like private healthcare, all contributing to higher HIV testing uptake.25,26 Partner education level, both husband and maternal education status (primary, secondary, and higher), particularly higher-level education, is a significant contributing factor for the disparity in HIV testing uptake. This suggests that children of more educated mothers who are disproportionately located in urban areas are more likely to be tested. Therefore, community-based awareness campaigns and targeted health promotion interventions can help bridge knowledge gaps. The finding is agreed with previous studies.10,27 Educated individuals have better understanding of HIV testing importance, leading to improved knowledge, favorable attitudes, and increased healthcare-seeking behavior. 28 Therefore, initiation of education is a target intervention to increase HIV testing and narrow disparity. Age of mother within 40-44 years and 45-49 years were significantly contributing to the disparity of HIV testing. The result is supported by previous study. 29 This association is a result of multiple interconnected factors. Older mothers often hold differing attitudes and health-seeking behaviors, including stigma surrounding HIV testing or a perception screening is irrelevant in later reproductive years. Additionally, they face physical barriers, such as comorbidities or reduced mobility, alongside economic challenges.30,31 Refused consent negatively influenced testing uptake due to fear of stigma and discrimination. Caregivers often decline testing to avoid perceived HIV status disclosure, social rejection, or community isolation of their children.10,24 Moreover, premarital HIV testing also enhances disparity of testing as well as HIV testing rate. These findings suggest that differences in these factors between rural and urban populations help narrow the gap, and supported with studies done in Sub-Saharan Africa. 23 The underlying reason relates to cultural sensitivity, as premarital testing is often perceived as an indication of potential health risks or stigmatized behaviors. The age of the child, specifically the 5–14-year-old category, significantly contributes to the disparity in HIV testing uptake. This highlights the need to strengthen early childhood HIV testing strategies in rural setting. It is also, finding is consistent with previous research indicating that older children are more likely to be tested due to increased health. 32 The number of children equal to or greater than five in the household had a significant positive contribution to HIV testing uptake. Indicating that larger households more common in rural settings face additional barriers to accessing health services. The finding is aligned with previous studies.23,33,34 The possible justification is that large family sizes have an impact on health care access.
Conclusion
This study revealed a substantial urban–rural disparity in pediatric HIV testing uptake in Ethiopia, with children in rural areas significantly less likely to be tested than those in urban areas. Approximately half of the disparity was explained by differences in population characteristics, while the remaining half was attributable to differences in how these characteristics influence testing uptake.
Thus, wealth status, maternal, household size, child age, and parental education were drivers of the disparity. Conversely, factors such as premarital HIV testing, consent refusal, and older maternal age showed disparity-reducing effects, suggesting potential leverage points for intervention. Reducing urban–rural disparities in pediatric HIV testing requires targeted strategies addressing both structural and behavioral factors, including improved rural access, community outreach, health education, and reduction of socioeconomic inequalities.
Strength and Limitation
This study presents valuable insights for health policymakers into disparities in pediatric HIV testing uptake between rural and urban settings in Ethiopia, using data from the 2016 EDHS. It identifies and quantifies the key factors influencing HIV testing uptake and contributing to urban–rural disparities in Ethiopia. Despite its strengths, including a large sample size and comprehensive data collection, the use of self-reported data may have introduced social desirability bias, recall and misclassification bias due to misunderstanding among respondents. However, the EDHS uses standardized questionnaires and trained interviewers to help minimize these potential biases. Since the study had a cross-sectional design, it could not establish causality. Variables were chosen based on availability of EDHS dataset and pervious literature while some variable such as maternal HIV status, antenatal care attendance, maternal HIV status facility delivery and other facility related factors did not include due to not availability or had substantial missing data in the EDHS dataset. The exclusion of these variables may have resulted in residual confounding. In addition, because the study used 2016 EDHS data, the findings may not fully reflect the current disparity in HIV testing uptake. Although testing strategies have evolved since 2016, the findings remain relevant for understanding persistent socioeconomic and urban–rural disparities.
Supplemental Material
Supplemental Material for Urban-Rural Disparities in Pediatric HIV Testing Uptake in Ethiopia: A Cross-Sectional Analysis of the 2016 Ethiopian Demographic and Health Survey by Tihtna Alemu, Lakew Asmare, Gebeyehu Lakew, Amlaku Nigussie Yirsaw, Zeamanuel Anteneh Yigzaw, Eyob Getachew in Journal of the International Association of Providers of AIDS Care (JIAPAC).
Acknowledgments
We would like to extend our gratitude to different workforces that participated in the 2016 Ethiopian Demographic and Health Survey and those who allowed us to access the data sets from the MEASURE DHS website. This manuscript was not registered as a clinical trial; thus, no clinical trial registration number is applicable.
Appendix.
Abbreviations
- AIDS
Acquired Immune Deficiency Syndrome
- ART
Anti-Retroviral Therapy
- CLHIV
Children Living with HIV
- EDHS
Ethiopian Demographic and Health Survey
- EMOH
Ethiopian Ministry of Health
- EPHIA
Ethiopian Population-based HIV Impact Assessment
- ESS
Ethiopian Statistical Service
- HIV
Human Immunodeficiency Virus
- ICF
International Classification of Functioning, Disability and Health
- UNAIDS
Joint United Nations Programme on HIV/AIDS
Authors’ Contributions: TA, LA, ZAY, ANY, EG, & GL played a vital role in the conceptualization, data acquisition, data processing, data analysis, software, and validation. TA, LA, & EG made a great contribution to report writing, drafting, and revising the manuscript. All the authors critically reviewed and approved the manuscript.
Funding: The authors received no financial support for the research, authorship, and/or publication of this article.
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Supplemental Material: Supplemental material for this article is available online.
ORCID iDs
Tihtna Alemu https://orcid.org/0009-0000-9233-841X
Lakew Asmare https://orcid.org/0009-0006-0455-9460
Ethical Considerations
This study used secondary, de-identified data from the 2016 EDHS, conducted by the ESS in collaboration with International Classification of Functioning, Disability and Health (ICF).
Consent to Participate
The original survey received ethical approval from the Ethiopian Public Health Institute (EPHI) and the ICF Institutional Review Board, written informed consent was obtained from all participants. Permission to access and use the dataset for this secondary analysis was obtained from the DHS Program. As the data were anonymized and publicly available, no additional ethical approval was required. All procedures complied with the Declaration of Helsinki.
Data Availability Statement
All data and materials used for this study were obtained from the DHS program with a reasonable request. Thus, the one who needs the data supporting the findings of this study can get it in anonymized form from URLs: https://dhsprogram.com/data/.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplemental Material for Urban-Rural Disparities in Pediatric HIV Testing Uptake in Ethiopia: A Cross-Sectional Analysis of the 2016 Ethiopian Demographic and Health Survey by Tihtna Alemu, Lakew Asmare, Gebeyehu Lakew, Amlaku Nigussie Yirsaw, Zeamanuel Anteneh Yigzaw, Eyob Getachew in Journal of the International Association of Providers of AIDS Care (JIAPAC).
Data Availability Statement
All data and materials used for this study were obtained from the DHS program with a reasonable request. Thus, the one who needs the data supporting the findings of this study can get it in anonymized form from URLs: https://dhsprogram.com/data/.