The biology behind the problem is unforgiving. In genetically susceptible individuals carrying the HLA-DQ2 or HLA-DQ8 variants, dietary gluten triggers an adaptive immune cascade in which the enzyme tissue transglutaminase-2 chemically modifies gliadin peptides, provoking T-cell-driven destruction of the small intestinal lining. The result is villous atrophy and crypt hyperplasia, which shrink the absorptive surface of the gut and compromise the epithelial barrier. Diagnosis still requires positive serology, typically tissue transglutaminase IgA antibodies, together with a small-intestinal biopsy demonstrating villous damage, yet many people who self-diagnose or drift onto gluten-free diets have never been formally tested. Survey data suggest a global prevalence of about 1.4 percent, but an iceberg effect means most cases remain undiagnosed, and athlete-specific figures are almost nonexistent.

The numbers that do exist are telling. In a survey of 141 NCAA collegiate athletes, roughly 2.8 percent reported a physician diagnosis of celiac disease, while about 11.3 percent scored above the threshold for celiac-consistent symptoms, yielding odds of high-symptom status nearly 18 times higher than a general-population benchmark. The authors of the review caution that these figures rely on self-report, were drawn from a small convenience sample skewed toward white Midwestern athletes, and were compared against general-population rather than age-matched non-athlete controls. Still, the signal is hard to ignore, particularly because intense endurance exercise independently raises intestinal permeability, elevates serum zonulin, and upregulates the pore-forming tight junction protein claudin-2, mechanisms that converge with celiac pathology and could amplify risk or mask symptoms in genetically susceptible athletes through what researchers call Exercise-Induced Gastrointestinal Syndrome.

Even after diagnosis, the challenges multiply. The gold-standard treatment, a strict gluten-free diet, is nutritionally treacherous for people whose energy demands can reach 50 to 80 kilocalories per kilogram of body weight per day in endurance sports. Gluten-free products are frequently made from refined rice, tapioca, and potato starches, carry a higher glycemic index than wheat equivalents, and lack the iron and calcium fortification of conventional foods. Cross-contamination is a persistent hazard: studies of restaurant meals labeled gluten-free have found that roughly a third contain detectable gluten, and sensitive patients can suffer mucosal injury at daily exposures as low as 10 milligrams. The socioeconomic burden compounds the problem, with gluten-free foods costing 76 to 518 percent more than conventional equivalents in the United Kingdom, roughly double in Saudi Arabia, and up to 259 percent more on average in the United Arab Emirates, a burden that falls hardest on young, underfunded athletes who report food-related anxiety, social isolation, and meals skipped before competition.

The nutritional consequences are measurable and severe. Iron deficiency anemia affects up to 82 percent of celiac patients, and only about half restore their iron stores within a year of starting the gluten-free diet. Exercise compounds the deficit because the hormone hepcidin, which blocks iron absorption, remains elevated for up to six hours after training, cutting fractional iron absorption by more than a third. The review recommends timing iron-rich meals and supplements to the early morning, avoiding the three-to-six-hour post-exercise window, and pairing plant-based iron sources with vitamin C. Vitamin D deficiency, present in 8 to 88 percent of celiac patients, carries a staggering 23.3-fold higher risk of fifth metatarsal stress fractures at low serum levels, prompting suggested intakes of 2,000 to 6,000 IU per day for affected athletes. Calcium, magnesium, zinc, and B vitamins follow similar patterns of depletion driven jointly by malabsorption and the poor nutrient density of gluten-free substitutes.

The review also ventures into emerging territory. Sucrosomial iron formulations are preferred for athletes who cannot tolerate ferrous sulfate, and magnesium citrate or glycinate outperform oxide, whose bioavailability is a mere 4 percent. Genetic polymorphisms in the vitamin D-binding protein and receptor genes may explain why some athletes need substantially larger doses to reach the same serum 25-hydroxyvitamin D target of 30 to 50 nanograms per milliliter. On the supplement front, multi-strain probiotics containing Bifidobacterium breve and Lactobacillus plantarum reduced gastrointestinal symptoms 29 percent more than placebo in meta-analysis, while the alanyl-glutamine dipeptide, which survives gastric digestion and upregulates the tight junction proteins claudin and occludin, shows theoretical promise for a gut battered both by disease and by exercise-induced ischemia, though no trial has yet tested it in celiac athletes.

Perhaps the most underappreciated dimension is psychological. A meta-analysis found that people with celiac disease face roughly six-fold higher odds of anxiety and more than double the odds of depression, and collegiate athletes with more celiac-consistent symptoms reported poorer quality of life across physical, psychological, social, and environmental domains, along with greater depression and perceived stress. Childhood celiac disease carries a 19 percent increased risk of psychiatric disorder that persists into adulthood. Disordered eating is another red flag, with a pooled prevalence of nearly 9 percent and a significantly elevated risk of anorexia nervosa, a dangerous overlap in athletic populations where restrictive eating is already common. Even cognition is affected: neuroimaging studies have documented slower reaction times and white matter microstructural changes, the so-called brain fog, with direct implications for tactical decision-making and reaction-time precision in sport.

To bring order to this fragmented picture, the authors lay out a monitoring architecture that spans serology, biochemistry, and performance. Tissue transglutaminase IgA with total IgA remains the first-line screen, and clinicians are urged to test athletes presenting with unexplained fatigue, recurrent infections, refractory iron deficiency, or disproportionate stress fractures, noting that classic gastrointestinal symptoms may be absent in up to half of atypical cases. HLA-DQ2/DQ8 genotyping, with a negative predictive value above 99 percent when both alleles are absent, helps when athletes have already gone gluten-free. Blood sampling should be standardized, ideally in the morning after at least 48 hours of rest, to control for exercise-induced analytical variation, a detail routinely neglected in clinical practice. Dual-energy X-ray absorptiometry tracks bone mineral density and distinguishes genuine fat-free mass recovery from the fat gain and sarcopenic pattern that has been observed after a year on a gluten-free diet, while countermovement jump, handgrip strength, VO2 max, heart rate variability, and patient-reported symptom and quality-of-life scales complete the functional picture.

The review is candid about its limits. It is a structured narrative review conducted under the SANRA quality framework, not a systematic review with risk-of-bias assessment or meta-analysis, and much of its practical guidance extrapolates from the general celiac population, athletic populations without the disease, and mechanistic studies rather than from trials in biopsy-confirmed celiac athletes, of which there are almost none. Its recommendations should therefore be read as hypothesis-generating and practice-oriented rather than graded clinical guidelines. Still, the authors argue that no existing review has previously woven nutritional assessment, supplementation, and performance monitoring into a single athlete-centered framework, and they call for randomized controlled trials with biopsy-confirmed enrollment, adherence-verified comparator arms, and stratification by sport type, sex, age, and mucosal healing status.

The broader message resonates beyond the locker room. Celiac disease sits at the intersection of immunology, gastroenterology, exercise physiology, and psychology, and athletes amplify every one of those variables. If future research confirms that the physiological stress of training lowers the threshold for disease expression in genetically susceptible individuals, sports medicine will need athlete-specific epidemiology, screening checklists, and possibly an international registry to track adherence, biomarkers, and performance over time. For now, the review offers coaches, dietitians, and team physicians a practical warning: when an athlete’s engine keeps misfiring for reasons that training loads and talent cannot explain, it may be worth checking whether the fuel line itself is under attack.

Subject of Research: Integrated nutritional and performance monitoring for athletes with celiac disease

Article Title: An Integrated Nutritional and Performance Monitoring Framework for Athletes with Celiac Disease: A Structured Narrative Review

Article References: Yamani, O. B., Alghamdi, M. M., Zagzoog, A. M., Noorwali, E. A., Alotaibi, R. A., Alghannam, A. F., Aljaloud, K. S., Aragon, A. A., & Elsahoryi, N. A. (2026). An Integrated Nutritional and Performance Monitoring Framework for Athletes with Celiac Disease: A Structured Narrative Review. Current Research in Food Science, Article 101568. https://doi.org/10.1016/j.crfs.2026.101568

Image Credits: AI Generated

DOI: Not provided

Keywords: celiac disease, athletes, sports nutrition, gluten-free diet, iron deficiency, vitamin D, intestinal permeability, micronutrients, performance monitoring, probiotics, glutamine, athlete health

The research, published in BMC Health Services Research, was led by Daniel Gudina, Gudeta Ayele, Behailu Hawulte and Ibsa Mussa from the School of Public Health at Haramaya University’s College of Health and Medical Sciences. The team set out to answer a deceptively simple question: what determines whether health workers in public facilities actually use the data flowing through DHIS2? This question matters because data utilization is one of the key functions of any health information system. When performance monitoring teams can read and interpret their own data, they can identify gaps in immunization coverage, spot outbreaks earlier, allocate staff and supplies more rationally and ultimately improve the quality of health service delivery. When they cannot, or do not, the entire investment in digital infrastructure risks becoming an expensive exercise in data entry without insight.

To investigate, the researchers conducted an institutional-based cross-sectional study between June 1, 2020 and July 31, 2020. They used a stratified sampling technique to select 220 participants working in public health facilities across the two administrative areas of eastern Ethiopia. Data collection relied on a structured questionnaire complemented by an observational checklist, allowing the team to capture both what health workers reported about their practices and what could be verified on the ground. The completed questionnaires were thoroughly checked, coded and entered into Epi-data 3.1 before being transferred to Stata 14 for statistical analysis. To identify the factors associated with data utilization, the researchers applied a binary logistic regression model, treating results as statistically significant when the p value fell below 0.05 with 95 percent confidence intervals.

The headline finding is sobering. Overall utilization of data from DHIS2 stood at about 45 percent, with a 95 percent confidence interval ranging from 39 to 50 percent. That figure falls well below the national recommended threshold, which calls for more than two-thirds of health facilities to be actively using their routine health information data for decision making. In other words, even in a system where the software has been deployed and staff have been trained to feed it, a majority of facilities are not translating the numbers into action. The study also notes that prior research across Ethiopia has reported significant variability in DHIS2 data utilization, suggesting that this is not a local anomaly but a systemic challenge with roots that vary from place to place.

What, then, separates the facilities that use their data from those that do not? The regression analysis identified four independent determinants, and each one is revealing. The first is attitude. Health workers who held a favorable attitude toward data use were roughly three times more likely to utilize DHIS2 data, with an adjusted odds ratio of 3.0 and a 95 percent confidence interval of 1.90 to 8.62. Attitude, in this context, reflects whether staff believe that reviewing data is worth their time, whether they see it as relevant to their daily work and whether they feel that acting on evidence is part of their professional identity. A health worker who views monthly data review as a bureaucratic chore will behave very differently from one who sees it as a diagnostic tool for improving services.

The second determinant is perceived self-competence. Workers who felt confident in their ability to interpret and apply the data were nearly three times more likely to use it, with an adjusted odds ratio of 2.9 and a confidence interval of 1.14 to 7.38. This finding speaks to a well-documented problem in health information systems across low- and middle-income countries: staff may be trained to enter data but not to analyze it. DHIS2 offers dashboards, pivot tables and visualization tools, but these features are only useful to people who understand what the outputs mean and how they connect to programmatic decisions. Self-doubt, in this environment, becomes a silent barrier. A nurse or health officer who feels incompetent with data will avoid opening the very reports that could guide their work, and the avoidance reinforces the incompetence in a self-perpetuating cycle.

The third and strongest single factor was perceived data quality. Health workers who believed the data in the system were accurate, complete and timely were more than four times as likely to use them, with an adjusted odds ratio of 4.4 and a confidence interval of 1.76 to 10.9. This is perhaps the most intuitive of the findings, and also the most troubling. If staff suspect that the numbers in DHIS2 are riddled with errors, duplicates or gaps, they will reasonably distrust any conclusion drawn from them. Data quality and data use are locked in a feedback loop: poor quality suppresses use, and without use there is little incentive or feedback mechanism to correct quality problems. Breaking that loop requires deliberate investment in data verification, feedback to data enterers and a culture in which accuracy is valued and rewarded rather than assumed.

The fourth determinant was supportive supervision. Facilities whose staff received supportive supervision were more than four times as likely to use DHIS2 data, with an adjusted odds ratio of 4.3 and a confidence interval of 1.48 to 12.45. Supportive supervision, in the language of the Performance of Routine Health Information System framework, known as PRISM, means supervisors who do more than inspect forms. They review data with frontline staff, help troubleshoot technical problems, encourage discussion of trends and connect the numbers to concrete service improvements. The PRISM framework, which underpins much of the conceptual thinking in this field, holds that technical, behavioral and organizational determinants together shape whether routine health information systems deliver value. The Ethiopian findings map neatly onto that framework: attitude and self-competence are behavioral determinants, perceived data quality is a technical one, and supportive supervision is organizational.

The implications for policy are direct. Ethiopia’s Federal Ministry of Health has invested substantially in DHIS2 as the backbone of its routine health information system, and the platform is expected to increase the utilization of health data nationwide. But the study’s results suggest that software deployment alone does not close the gap between data availability and data use. Interventions should target the four determinants identified: building favorable attitudes toward evidence-based practice, strengthening the analytical self-competence of health workers through practical mentorship rather than one-off training, assuring and communicating data quality so that staff trust what they see, and institutionalizing supportive supervision so that every facility benefits from regular, constructive engagement around its own numbers. The performance monitoring teams that exist in Ethiopian facilities could become the natural vehicle for this work, provided they are equipped and encouraged to function as intended.

There is also a broader lesson for the global health informatics community. DHIS2 is now used in dozens of countries, and the dream of a digital health information backbone is closer to reality than ever. Yet the eastern Ethiopia study is a reminder that the last mile of any information system is human. A dashboard nobody opens is indistinguishable from a filing cabinet nobody opens. The researchers, whose work was financially supported by the Doris Duke Charitable Foundation as part of the Capacity Building and Mentorship Program project, with no funder role in study design or interpretation, obtained ethical clearance from Haramaya University’s Institutional Health Research Ethics Review Committee in accordance with the Helsinki II declaration. Their message to health systems everywhere is clear: to unlock the value of digital health data, invest as much in confidence, trust and supervision as in servers and software. Until the people closest to the data believe in its quality and in their own ability to act on it, the numbers will keep flowing, and the decisions will keep waiting.

Subject of Research: Determinants of District Health Information System 2 data utilization among health workers in public health facilities in eastern Ethiopia

Article Title: Determinants of district health information system 2 data utilization in public health facilities in Harari Regional States and Dire Dawa City Administration, Eastern Ethiopia

Article References: Determinants of district health information system 2 data utilization in public health facilities in Harari Regional States and Dire Dawa City Administration, Eastern Ethiopia. (n.d.). https://doi.org/10.1186/s12913-026-15620-w

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15620-w

Keywords: DHIS2, health information systems, data utilization, Ethiopia, public health facilities, health informatics, supportive supervision, data quality, evidence-based decision making, routine health information systems, Haramaya University, performance monitoring