OETDK.

Introduction: Nigeria has highest malaria burden. The disease, transmitted through the bite of an infected female Anopheles mosquito, remains a major public health challenge. In 2023, the World Health Organisation reported approximately 263 million malaria cases and 597,000 malaria deaths across 83 endemic countries. Nigeria alone accounted for an estimated 68 million cases, representing one of the highest national burdens worldwide. Objectives and Hypotheses: This study aims to assess the burden, determinants, and control strategies of malaria among adults residing in Abuja, Nigeria, with a focus on environmental and behavioural factors influencing malaria incidence. Methods: A cross-sectional study was conducted among 308 Abuja residents aged ≥18 years, including pregnant women and parents or guardians of children under five. Data were collected using a structured online questionnaire developed by the researcher, capturing sociodemographic characteristics, malaria history, environmental exposures, preventive practices, access to healthcare, and malaria control strategies. Chi-squared tests assessed associations between malaria incidence in the previous month and explanatory variables. Binary logistic regression identified independent predictors of malaria incidence. Data were analysed using STATA IC version 17.0. Outcomes: Of the 308 participants, 159 (51.6%) were female. A total of 115 respondents (37.3%) reported malaria in the last month, with most cases occurring during the rainy season (106; 44.4%). Malaria incidence was significantly associated with place of residence (p=0.015), season (p<0.001), proximity to stagnant water (p=0.005), mosquito net use (p=0.004), wastewater disposal methods (p=0.002), and regular indoor spraying (p=0.029). Logistic regression showed that the presence of stagnant water near the household increased the odds of malaria (OR=1.96; 95% CI: 1.04–3.70; p=0.037), while proper wastewater disposal reduced the odds (OR=0.42; 95% CI: 0.20–0.86; p=0.018). Conclusion: Malaria is common in Abuja due to environmental conditions, but improved sanitation and greater use of prevention methods can reduce it.

Témavezető: Dr. Ulambayar Battamir

Introduction: Sleep quality is a vital aspect of overall health influencing physical, cognitive, and emotional functioning. Poor sleep quality is common in university students, who face various academic, social, and lifestyle challenges that may increase risk of sleep disturbances.Objectives: This study assessed sleep quality in international students at the University of Debrecen, Hungary and examined its association with demographic, lifestyle, and socioeconomic factors.Methods: This cross-sectional study included 364 international students. Sleep quality was assessed using the validated Pittsburgh Sleep Quality Index (PSQI). The PSQI score ranges from 0-21, with scores ≤5 indicating good sleep quality, and >5 indicating poor sleep quality. Descriptive statistics summarized participant characteristics while Chi-square, Mann–Whitney U, and Kruskal–Wallis tests assessed associations. Binary logistic regression was performed to identify the predictors of poor sleep quality. Data analysis was performed using STATA IC version 17.0.Outcomes: The median PSQI score was 10 (IQR 7-13), indicating high prevalence of poor sleep quality (82.7%). Sleep quality was significantly associated with course type, smoking, physical activity, fruit and vegetable consumption, parental education, financial concerns, monthly allowance, social media use, delayed bedtime due to social media use, and primary smartphone activity (p<0.05). Using logistic regression, frequent financial concerns compared to no concerns (OR=37.5, 95% CI:6.02-234.76) and delayed bedtime due to social media use compared to no delayed bedtime (OR= 3.15, 95% CI: 1.01-9.80; OR=6.09, 95% CI: 1.73-21.41; OR= 7.32, 95% CI: 1.66-32.25) were significant risk factors of poor sleep quality. In contrast, studying computer sciences compared to medical/health sciences (OR= 0.19, 95% CI: 0.07-0.55), graduate parental education compared to bachelor parental education (OR=0.33, 95% CI: 0.14-0.77), and using smartphones for academic work compared to gaming/web browsing (OR= 0.20, 95% CI: 0.05-0.92) were significant protective factors against poor sleep quality.Conclusion: Poor sleep quality is highly prevalent among international students and is significantly influenced by socioeconomic and lifestyle factors.

Témavezető: Dr. Battamir Ulambayar

Introduction: Child health plays a foundational role in human development, yet disparities in access to essential healthcare services persist across Sub-Saharan Africa (SSA), disproportionately affecting children from marginalized ethnic and racial groups. These inequalities contribute to preventable morbidity, undernutrition, and mortality among children under five, despite global efforts to promote equitable health coverage.Aims: This systematic review aimed to examine and synthesize existing evidence on racial and ethnic disparities in childhood healthcare access in SSA. It focused on how ethnic identity influences access to immunization, child survival outcomes, and nutritional status, while also identifying the structural and cultural mechanisms that sustain these inequalities.Methods: A systematic search of PubMed for studies published between 2010 and 2025 was conducted using relevant MeSH terms and Boolean operators. Inclusion criteria focused on studies examining racial or ethnic differences in childhood healthcare access in SSA. A total of 2,030 records were screened, 97 full-text articles assessed, and 10 studies meeting all criteria were included. Study selection followed PRISMA guidelines.Results: Across the reviewed studies, ethnicity consistently emerged as an independent predictor of childhood healthcare inequities. Vaccination rates were significantly lower among children from marginalized ethnic groups such as the Hausa/Fulani in Nigeria and Somali and Luhya communities in Kenya, compared to dominant groups such as the Igbo, Yoruba, and Kikuyu.Similarly, child mortality was higher in groups experiencing socioeconomic deprivation and restricted maternal healthcare access. Nutritional outcomes also varied substantially by ethnicity, with some groups experiencing markedly higher odds of stunting and underweight even after controlling for wealth and education.Conclusions: Racial and ethnic disparities in child healthcare access in SSA are driven by intersecting structural, geographical, and cultural barriers. While socioeconomic improvement reduces some inequalities, it does not eliminate them, indicating that ethnic identity continues to shape health outcomes independently. Addressing these disparities requires strengthening culturally inclusive healthcare delivery, improving access in underserved regions, and integrating ethnicity-disaggregated monitoring into national health systems.

Témavezető: Dr. Sárváry Attila

Introduction: According to the international diabetes federation Europe, 1 out of 3 diabetic patients develop chronic kidney disease in their lifetime. Early recognition of signs related to chronic kidney disease (CKD) and accompanying comorbidities is crucial to slow down deterioration of kidney function. When coupled with timely management, it improves patient prognosis, reduces morbidity and over all burden of the disease. Objective: To identify factors and their temporal influence on the onset of chronic kidney disease in type 2 diabetic patients.Methods: A dataset of 21,069 patients over 15 years follow up was obtained from a Hungarian hospital. The recorded occurrences of the outcome in focus, chronic kidney disease, were 3,984 (18.9% of patients). The continuous predictors were standardized using Z-scores and collinearity was assessed using VIF > 5. Initially 1,197 variables were processed through variance filtering, Univariate Cox screening and Elastic Net Penalized Cox to get the final 38 factors on which multi-variable cox regression model was used.Outcomes: The results show that patients with comorbidities like essential hypertension and abnormal uric acid metabolism carry a 42% (HR 1.42; CI 95%, 1.32-1.54) and 57% (HR 1.57; CI 95%, 1.41-1.74) increased risk, respectively, of developing chronic kidney disease. While diagnoses like anemia of chronic disease (HR 2.01; CI 95%, 1.79-2.27) and chronic tubulo-interstitial nephritis (HR 2.09; CI 95%, 1.79-2.43) can double the likelihood of chronic kidney disease. Conclusion: The proper identification of certain diagnosis during follow up of type 2 diabetic patients has a statistically significant predictive value regarding the onset of chronic kidney disease. These comorbidities can be managed timely to prevent grave complications and premature death.

Témavezető: Dr. Bata Róbert

Introduction:Suicide remains a major public health issue. Recent social changes, including those during the COVID-19 period, affected stress levels and access to care. Combining national mortality trends with autopsy data may clarify current demographic and clinical suicide patterns.Objective:To assess yearly suicide-to-all-death ratios in Hungary (2018–2023) and examine demographic, behavioural, and clinical characteristics of autopsy-confirmed suicides from two counties.Methods:National suicide proportions were analysed, and county cases (n=210) were evaluated for demographic and clinical factors using Chi-square. County–national suicide proportions were compared with two-proportion z-tests. Monthly trend similarity was assessed with Pearson correlation; seasonal distributions with chi-square goodness-of-fit.Results:National suicide ratios varied significantly, declining from 1.26% in 2018 to 1.00% in 2021 and rising to 1.24% in 2023 (p=7.75×10^-11). County-level autopsy counts also fluctuated significantly (p=0.0448). Males represented 76% of cases, with peaks in ages 50–59 and ≥70. Method differed by gender, with males more often using violent means and females more often poisoning (p<10^-35). Age showed similar differences (p<0.001). Place of death varied by gender and method (p<10^-60). Psychiatric comorbidity and previous attempts were more common in females and poisoning cases (p<10^-16 and p<10^-26). Medical comorbidity differed by gender (p<10^-11). Across 2018–2023, suicide proportions were higher than national averages in Hajdú-Bihar (1.45%; p=6.9×10^-7) and Szabolcs-Szatmár-Bereg (1.31%; p=0.0125), consistent with raw counts. Monthly suicide percentages strongly correlated with national trends (Hajdú-Bihar r≈0.49; Szabolcs-Szatmár-Bereg r≈0.54; both p<0.001), and seasonal patterns did not differ (Hajdú-Bihar p=0.72; Szabolcs-Szatmár-Bereg p=0.29).Conclusions:National and county-level data showed significant temporal variation. County suicides exceeded national proportions, but monthly patterns closely matched national seasonal trends. Clear method-, gender-, and age-linked patterns, along with differences in comorbidity and previous attempts, highlight key targets for regional suicide prevention.

Témavezető: Dr. Németi Balázs

A táplálkozási zavarok napjaink egyik legsúlyosabb és legösszetettebb mentális egészségügyi problémáját jelentik. Ezek a kórképek nemcsak a táplálkozási magatartás torzulásával járnak, hanem mélyen érintik az egyén testképét, önértékelését és pszichés működését is. Különösen veszélyesek, mert gyakran más mentális betegségekkel együtt, komorbid módon jelentkeznek, és a depresszió, szorongásos vagy személyiségzavar fennállása jelentősen rontja a prognózist, növeli a visszaesés és mortalitás kockázatát, valamint megnehezíti a terápiás beavatkozásokat.A kutatás célja az volt, hogy feltárjuk a táplálkozási zavarok és más mentális betegségek közötti összefüggéseket, valamint megvizsgáljuk, hogy az evészavar megléte miként befolyásolja az egyéb pszichiátriai kórképek hosszú távú kimenetelét.Tanulmányunk a Debreceni Egyetem Klinikai Központja 2007–2022 között gyűjtött kórházi nyilvántartásain alapuló retrospektív longitudinális elemzés. A kezdeti adatkészlet 333 807 beteg adatait tartalmazta, összesen 805 989 kórházi feljegyzéssel, amelyek a résztvevők vizsgálati és ellátási eseményeit reprezentálták. A betegségek az orvosok által rögzített BNO-10 kódok alapján kerültek azonosításra. A túlélésanalízist többféle módszerrel végeztük: Kaplan–Meier görbék, Log-rank próbák, Nelson–Aalen kumulatív hazard-becslés, valamint Cox- regressziós modellek alkalmazásával.Az eredményeket a veszélyhányados (VH) és a hozzá tartozó 95%-os megbízhatósági tartomány (95% MT) alapján értékeltük. A női nem szignifikánsan növelte a depresszió kialakulásának kockázatát (VH = 1,32; 95% MT [1,26–1,39]; p < 0,001), a bipoláris zavar esetén pedig védő tényezőnek bizonyult (VH = 0,92; 95% MT [0,86–0,99]; p = 0,019). Az evészavar megléte pedig kiemelten erős kockázatnak bizonyult, több mint négyszeres rizikónövekedést a depresszió megjelenésére (VH = 4,23; 95% MT [2,11–8,46]; p< 0,001) a bipoláris zavar esetén pedig több mint ötszörös kockázatot jelent (VH = 5,45; 95% MT [2,59–11,44]; p < 0,001).Eredményeink alapján az evészavarok a depresszió, valamint a bipoláris zavar kialakulásának meghatározó kockázati tényezői. Mivel a táplálkozási zavarok komplex, krónikus lefolyású betegségek, gyakran igényelnek kórházi és pszichiátriai ellátást, ezért korai felismerésük, megelőzésük és integrált kezelésük alapvető a mentális egészség javítása és az egészségügyi rendszer terheinek csökkentése érdekében.

Témavezető: Dr. Ghanem Amr

BackgroundHypertension remains a leading modifiable risk factor for global morbidity and mortality, responsible for approximately 7.5 million deaths annually. Accurate risk prediction is critical for guiding targeted interventions. While logistic regression (LR) models are well-established and highly interpretable, advanced machine learning techniques—particularly Extreme Gradient Boosting (XGBoost)—show promise in enhancing predictive performance. However, questions persist about the trade-off between accuracy and interpretability in clinical settings. The objective of this study was to compare the performance of LR and XGBoost in predicting hypertension risk, placing equal emphasis on their predictive performance and interpretability.MethodsThis retrospective study analyzed 15,564 individual records pooled from three waves of the Hungarian European Health Interview Survey (EHIS). Explanatory variables included sociodemographic and economic factors, lifestyle behaviors, and health conditions. Two predictive models were developed: a standard logistic regression and an XGBoost model. Performance was evaluated using area under the ROC curve (AUC), accuracy, precision, recall, and F1 score. A grid search approach was employed to optimize XGBoost’s hyperparameters.ResultsThe XGBoost model demonstrated higher accuracy (81.82% vs. 80.06%) and recall (90.60% vs. 80.61%) compared to logistic regression. It also outperformed LR in F1 score (81.21% vs. 73.21%) and precision (73.58% vs. 67.06%). Interestingly, logistic regression offered a slightly higher AUC (89.65% vs. 88.07%) and superior feature interpretability.ConclusionsXGBoost exhibited superior predictive performance for hypertension risk, though logistic regression delivered marginally better AUC and clearer feature interpretation. Future large-scale, prospective studies should focus on refining both performance and interpretability to solidify the practical value of these models in clinical environments.

Témavezető: Dr. Ghanem Amr

KEYWORDS: residential segregation, breast cancer screening, cross-sectional study, inequality, monitoring, Covid-19Introduction: The participation in breast cancer screening (BCS) has been far below the recommendation among Hungarian women in the last decade. The socio-economic inequalities of the use of this preventive service have been extended in the same period.Objective: This study investigated the impact of the residential segregation and Covid-19 related health care use restrictions on the BCS coverage. The change of relative screening coverage in segregated and nonsegregated areas were investigated across the reference year of 2019, and in the two year affected by the Covid-19 epidemic (2020, 2021).Methods: Data covering the whole county from 2019, 2020, 2021 were obtained from the National Health Insurance Fund (NHIF). Segregated areas (SAs) were defined by geographical clustering of low-income and less-than-primary-education. Areas within settlements not belonging to SA were considered as non-segregated, complementary areas (CAs). The target group was composed of women aged 45–65, and BCS participation was evaluated as appropriate if the women participated in mammography within 2 years. Age- and eligibility for exemption certificate standardized participation ratios (sPRs) were calculated for each SA and CA. The level of inequality was quantified by the relative standardized participation ratio (rsPR) by comparing sPR in the SAs versus CAs.Results: Crude participation ratios in SAs aggregated for the whole country declined from 25.6% in 2019 and 21.7% in 2020 to 17.6% in 2021, while were markedly higher in complementary areas (42.5% in 2019, 43.6% in 2020, and 32.7% in 2021). The relative standardized participation ratios in SAs worsened progressively from rsPR2019=0.627 (95% CI 0.616–0.639) in 2019 to rsPR2020=0.612 (95% CI 0.599–0.625) and rsPR2021=0.552 (95% CI 0.539–0.565). While, 59,5% of the missing BCSs in SAs were attributable to the segregation in 2019, this etiological fraction increased to 63.3% in 2020 and 81.3% in 2021.Conclusion: This study demonstrated that BCS participation (1) was far below the required level in the general Hungarian population, (2) was reduced further during Covid-19 epidemic, and (3) was substantially and increasingly lower among women living in SAs. Our observations suggest reconsideration of BCS organization methodology.

Témavezető: Prof. Dr. Sándor János

Az elhízás napjainkra népbetegséggé vált, amely nemcsak számos krónikus, nem fertőző betegség következménye, hanem azok kialakulásának kockázati tényezője is. A Központi Statisztikai Hivatal adatai szerint a magyar felnőtt lakosság közel 60%-a túlsúlyos vagy elhízott (nők: 51%, férfiak: 65%), és ez az arány folyamatosan emelkedik. A túlzott, különösen a feldolgozott húsok fogyasztása kedvezőtlen egészségügyi hatásokkal járhat, ugyanakkor a hús fontos fehérje-, vitamin- és ásványianyag-forrás.A kutatás célja annak vizsgálata volt, hogy a testtömegindex (BMI) kategóriái hogyan befolyásolják a vörös, fehér és feldolgozott húsfogyasztás gyakoriságát a magyar lakosság körében.Kutatásunkhoz a 2019-es Európai Lakossági Egészségfelmérés magyarországi adatait használtuk, 5603 fő önbevalláson alapuló válaszait elemeztük. Logisztikus regressziós elemzést és khí-négyzet próbát végeztünk. Magyarázó tényezőink a testtömegindex kategóriák voltak (normál, túlsúly, elhízás), kimeneti tényezők pedig a vörös-, fehér-, és feldolgozott húsfogyasztás. Eredményeinket korrigáltuk a releváns szociodemográfiai és életmódbeli tényezőkre.Az elhízottak körében szignifikánsan nagyobb eséllyel fordult elő a vörös hús (EH = 1,17; 95% MT: [1,02–1,33]) és a feldolgozott hús fogyasztása (EH = 1,22; 95% MT: [1,06–1,40]), míg a fehér hús fogyasztása kisebb eséllyel (EH = 0,86; 95% MT: [0,76–0,96]) jelent meg a normál testsúlyúakhoz képest. A túlsúlyosak esetében a fehér hús fogyasztásának esélye szintén magasabbnak bizonyult (EH = 1,17; 95% MT: [1,03–1,32]). A női nem növelte a fehér hús fogyasztását (EH = 1,45; 95% MT: [1,29–1,63]), míg csökkentette a vörös húsét (EH = 0,49; 95% MT: [0,44–0,55]). Az aktív dohányzás a vörös (EH = 1,21) és a feldolgozott hús (EH = 1,19) fogyasztásának esélyét is növelte, míg a napi alkoholfogyasztás kizárólag a feldolgozott hús esetében mutatott pozitív kapcsolatot (EH = 1,34; 95% MT: [1,08–1,66]).Eredményeink alapján a magasabb testtömegindex kedvezőtlen húsfogyasztási mintázatokkal és egyéb egészségtelen életmódbeli tényezők együttes előfordulásával jár. Az egészségtudatos táplálkozást elősegítő intervenciók, például az Okostányér ajánlásainak alkalmazása, a zöldség- és gyümölcsfogyasztás növelése, valamint alternatív fehérjeforrások, mint a hüvelyesek étrendbe való bevezetése, hatékonyak lehetnek az elhízás megelőzésében és kezelésében is.

Témavezető: Ghanem Amr Sayed