Published in PLOS One on 2026-09-15, this study is presented as an attributed evidence briefing. The excerpts below are the original researchers’ words, reproduced under their Creative Commons Attribution licence. Health Signal has selected the abstract and, where needed, opening background paragraphs; the complete methods, results, limitations and references remain in the linked paper.
Original authors: Teresa Kisi Beyen, Edom Seife, Biniyam Tefera Deressa, Girma Taye, Adamu Addissie, Takele Gezahegn Demie
Source: PLOS One • DOI 10.1371/journal.pone.0357042
Read the complete primary study ↗ · Creative Commons Attribution licence
From the researchers
Abstract
In Ethiopia, according to the GLOBOCAN 2022 report, there were 1,494 cases of esophageal cancer and 1,422 deaths attributed to the disease. The incidence and mortality of esophageal cancer are projected to increase to 3,210 and 3,057 cases by 2040, respectively. Approximately 68.3% of the cases were reported from the Arsi and Bale Zones, which also had the highest disease burden and mortality. Thus, undertaking a thorough study to identify hotspot areas for local preventative and control actions is important.
To assess the spatial clustering of esophageal cancer in Central Oromia, Ethiopia.
A cross-sectional study design was employed to investigate the spatial clustering of esophageal cancer patients. Data were collected from records of 367 patients who visited four hospitals (namely, Tikur Anbessa Specialized Hospital, Adama Hospital Medical College, Asella Teaching and Referral Hospital, and Meda Walabu University General Hospital) between April 3, 2019, and August 25, 2025. The kebele, woreda, and zone of each patient were collected from the records and linked to Ethiopian shapfiles obtained from the Ethiopian Space Science and Geospatial Institute (SSGI). The spatial inequality of esophageal cancer was measured using the Gini coefficient; while spatial autocorrelation was assessed using Moran’s I. The risks within clusters were quantified using relative risk (RR) with its 95% confidence interval, as well as log-likelihood ratio (LLR) and p-values.
The annual incidence of esophageal cancer in the study area was 2.60 cases per 100,000 populations [95% CI: 2.34, 2.88]. The Gini coefficient revealed spatial inequality in the distribution of cases at both the district (G = 0.33; 95% CI: 0.24, 0.40) and kebele levels (G = 0.38; 95% CI: 0.33, 0.43). The Moran’s I showd significant positive spatial autocorrelation at the kebele level (I = 0.17, p-value = 0.037). The risk of developing esophageal cancer was high in Robe district [RR = 1.93; 95% CI: 1.43, 2.61; LLR = 6.82; p-value = 0.022], Robe 01 kebele [RR = 7.8; 95% CI: 4.57, 13.31; LLR = 16.35; p-value = 0.000024], and Kula 01 kebele [RR = 9.96; 95% CI: 4.45, 22.32; LLR = 8.35; p-value = 0.034]. In contrast, 17 districts [RR = 0.55; 95% CI: 0.41, 0.73; LLR = 9.31; p-value = 0.0051] and 52 kebeles [RR = 0.55; 95% CI: 0.41, 0.73; LLR = 0.87; p-value = 0.014] were identified as low-risk areas.
Esophageal cancer showed uneven spatial distribution and significant autocorrelation in the study area. The presence of both high- and low-risk areas indicated significant geographic disparities. Robe district had nearly twice the risk, Robe 01 kebele had more than seven times the risk, and Kula 01 kebele had nearly ten times the risk of developing esophageal cancer compared to other districts and kebeles, respectively. Allocating diagnostic resources to health facilities serving high-risk districts and kebeles, promoting community health education on modifiable risk factors, and investigating individual-level risk factors are required to explain the observed clustering patterns.
Reading this evidence
Use the full paper to check the study design, participant selection, comparator and outcome definitions before drawing a practical conclusion. An association does not by itself show cause and effect. A reported performance measure needs its denominator and uncertainty. A finding from a particular facility, sample or time period should retain that scope when it is discussed elsewhere.
This briefing makes the source accessible within the wider technology & industry desk. It does not assess an individual patient or certify a product. When considering relevance to another health system, examine the original authors’ account of context and limitations, then seek local implementation evidence. The related reporting below provides other studies to read alongside this one; it is a topic connection, rather than a claim that their results are directly comparable.
© 2026 Teresa Kisi Beyen, Edom Seife, Biniyam Tefera Deressa, Girma Taye, Adamu Addissie, Takele Gezahegn Demie. Excerpts reproduced under CC BY. Selection, formatting and contextual notes by Health Signal. The researchers are the authors of the source study, not members of Health Signal’s staff.
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