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Objective: This study’s objective was to identify the factors and impact of serums calcium 25-Hydroxy vitamin D, ferritin, uric acid, and sleeping disorders on benign paroxysmal positional vertigo (BPPV) patients. Methods: This is a case and control design study. The consecutive patients’ visits (age, older than 25 years) with idiopathic BPPV were recruited in the present study. For each patient, 3:1 sex and age-matched healthy people were assigned as the control. The study comprised 177 patients with BPPV and 656 controls. The study included biochemical, clinical, physical examinations, PSQI sleep quality, supine roll test, and Dix–Hallpike test for the diagnosis of all patients, and pure-tone audiometry (PTA) was used to assess hearing. Univariate and multivariate stepwise regression analyses were used for statistical analysis. Results: The study comprised 833 patients with 295 males (35.4%) and 538 females (64.6%) who were between 25 and 70 years old. Of a total of 833 participants, 177 were BPPV patients, and 656 subject were normal. The results shown that there were significant differences between the BPPV and the normal group in terms of BMI (p = 0.039), physical activity (p = 0.003), cigarette smoking (p = 0.035), nargile-waterpipe use (p < 0.001), diabetes (p < 0.001), hypertension (p < 0.001), congestive heart failure (CHF) (p < 0.001), neurology (p < 0.001), tinnitus (p < 0.001), dizziness (p < 0.001), headache (p < 0.001), vitamin D (p = 0.004), calcium (p = 0.004), magnesium (p < 0.001), potassium (p = 0.019), phosphorus (p < 0.001), haemoglobin (p < 0.001), serum glucose (p < 0.001), HbA1c (p < 0.001), triglyceride (p < 0.001), systolic BP (p = 0.004), diastolic BP (p = 0.008), and microalbuminuria (p = 0.005); ATP III metabolic syndrome (p = 0.038), IDF metabolic syndrome (p = 0.034), and poor sleep (p = 0.033). In terms of the type of BPPV, the posterior canal was the most commonly affected (n = 126, 71.2%), followed by the horizontal (n = 43, 24.3%) and anterior canal (n = 8, 4.5%). The analysis indicated that serum ferritin (p < 0.001), uric acid (p < 0.001), blood pressure (p < 0.001), dizziness (p < 0.001), cigarette–water-pipe smokers (p = 0.004), headaches/migraines (p = 0.005), calcium (p = 0.007), vitamin D deficiency (p = 0.008), sleepiness (p = 0.016), physical activity (p = 0.022), CHF (p = 0.024), and tinnitus (p = 0.025) were considered as risk predictors for BPPV. Conclusions: The results revealed that the serum levels of vitamin D, ferritin, uric acid, and calcium are low among the study population and supplementation could be considered as prevention in BPPV patients.

AimThis study aimed to investigate the causes and risk factors of colorectal cancer (CRC) in a Turkish population, focusing on various modifiable and non-modifiable risk factors.MethodsA hospital-based case-control design was employed to compare individuals with CRC (cases) to individuals without CRC (controls). Male and female participants were recruited from the surgery, internal medicine, and out-patient departments. The study encompassed socio-demographic data, clinical information, radiological diagnoses, and biochemical measurements. Univariable and multivariable logistic regressions were used to determine associated risk factors of CRC.ResultsThe study included 704 individuals with CRC and 704 controls. Significant socio-demographic disparities were observed between the groups, with over 30% of the cases having lower levels of education and income compared to the controls. Lifestyle factors such as obesity, higher rates of smoking (cigarettes and hookah) and alcohol consumption were more prevalent among cases than controls. Further significant associations were identified with intestinal inflammation, obesity, processed food consumption, and symptoms such as abdominal pain, cramps, diarrhea, constipation, blood in stool, bloating, irritable bowel syndrome, nausea/vomiting, anemia, stress, fatigue, weakness, and weight loss. Diet analysis revealed that individuals with CRC consumed more red meat, processed and fast foods along with less pulses and vegetables. Genetic predispositions and exposure to chemicals also correlated strongly with increased CRC risk. Multivariable regression analysis identified, nausea/vomiting, constipation, intestinal disease, genetics factor, hookah-nargileh use, history of any cancer, family history of bowel cancer, constipation, cigarette smoking, stress, milk-yogurt consumption, obesity and red meat consumption as significant determinants for CRC.ConclusionCRC risk is influenced by dietary, lifestyle, and genetic factors. Awareness of hereditary risk and participation in screening are crucial. Lifestyle changes, such as avoiding smoking, hookah, and alcohol use, and adopting a healthy diet, are essential for prevention.

Throughout history, armed conflicts have profoundly affected individuals and societies, with recent events in Ukraine, the Middle East, and beyond bringing into sharp focus the severe mental health and humanitarian consequences of geopolitical crises. Such situations often result in mass fatalities, destruction, displacement, forced migration, and other critical life events. Amid these scenarios, the adverse outcomes for mental health and well-being in both the short and long term must be emphasized. As a conceivable example of the latter, the proposed concept of intergenerational trauma could have far-reaching implications. In particular, in certain regions, civilians have repeatedly experienced instances of violence and may have continually been exposed to critical life events and traumatic stress. In this context, the consequences of these events for individual well-being and global mental health will likely be registered for years to come. Accordingly, urgent help and actions to address the mental health burdens within contemporary conflicts should be accentuated in humanitarian, political, and diplomatic interventions. Equally, health policies must adopt a long-term approach to support initiatives under the purview of global and public mental health objectives.

Since its inception, social media has brought about numerous benefits, including higher levels of social connectedness, potential positive interactions, and greater access to information. Nonetheless, the excessive use of social media can lead to negative health outcomes, such as social anxiety, depression, low self-esteem, reduced sleep quality, and higher perceived stress. It has been argued that boredom and loneliness may be mediating factors between social media misuse and negative mental health effects, above all among youth and adolescents. Likewise, exposure to graphic imagery or misinformation on social media may also have deleterious implications for mental health. Taken together, this suggests a need for targeted studies on the relationship between social media and mental health, as well as the development of educational interventions for adolescents to share knowledge about the safe use of such tools. Mental health professionals should be adequately trained in identifying risk factors and treating the negative health outcomes that may result from social media. Specific strategies and guidelines should be adopted by social media companies aligned with international evidence from health agencies and experts in e-mental health.

AimThis study explores the predictors and associated risk factors of sleep quality, quality of life, fatigue, and mental health among the Turkish population during the COVID-19 post-pandemic period.Materials and methodsA cross-sectional survey using multi-stage, stratified random sampling was employed. In total, 3,200 persons were approached. Of these, 2,624 (82%) completed the questionnaire package consisting of socio-demographic information, Pittsburgh Sleep Quality Index (PSQI), the WHO Quality of Life Brief Version (WHOQOL-BREF), Fatigue Assessment Scale (FAS), Patients Health Questionnaire (PHQ-15), GAD-7 anxiety scale, and the 21-item Depression, Anxiety, Stress Scale (DASS-21).ResultsSignificant differences between genders were found regarding socio-demographic characteristics (p < 0.01). Using PHQ-15 for depressive disorders, significant differences were found between normal and high severity scores (≥ 10), regarding age group (p < 0.001), gender (p = 0.049), educational level (p < 0.001), occupational status (p = 0.019), cigarette smoking (p = 0.002), waterpipe-narghile smoking (p = 0.039), and co-morbidity (p = 0.003). The WHOQOL-BREF indicated strong correlations between public health, physical health, psychological status, social relationships, environmental conditions, and sleep disorders (p < 0.01). Furthermore, comparisons of the prevalence of mental health symptoms and sleeping with PHQ-15 scores ≥ 10 (p = 0.039), fatigue (p = 0.012), depression (p = 0.009), anxiety (p = 0.032), stress (p = 0.045), and GAD-7 (p < 0.001), were significantly higher among the mental health condition according to sleeping disorder status. Multiple regression analysis revealed that DASS21 stress (p < 0.001), DASS21 depression (p < 0.001), DASS21 anxiety (p = 0.002), physical health (WHOQOL-BREF) (p = 0.007), patient health depression-PHQ-15 (p = 0.011), psychological health (WHOQOL-BREF) (p = 0.012), fatigue (p = 0.017), and environmental factors (WHOQOL-BREF) (p = 0.041) were the main predictor risk factors associated with sleep when adjusted for gender and age.ConclusionThe current study has shown that sleep quality was associated with the mental health symptoms of depression, anxiety, stress, and fatigue. In addition, insufficient sleep duration and unsatisfactory sleep quality seemed to affect physical and mental health functioning.

The aim of this study was to assess the rates of depression, anxiety, and stress and quality of sleeping among COVID-19 patients with and without type 2 diabetes mellitus (T2DM). A case and control design has been employed, involving patients affected by COVID-19 infection (884 with T2DM vs. 884 controls without T2DM) and hospitalized in Istanbul (Turkey) from January to December 2021. A multivariate stepwise regression approach was used to test the associations between sociodemographic, metabolic, serum markers, mental health scores, and T2DM/COVID-19 patients’ clinical presentation. A statistically significant difference between T2DM and non-T2DM was found with respect to age, gender, BMI (body mass index), smoking, physical exercise, and physical comorbidities as well as levels of depression, anxiety, stress, and sleeping disorders (0.0003 ≤ all p = 0.025). With regard to serum biomarkers, vitamin D and ferritin were identified as useful parameters of reduction of glycated hemoglobin as well as COVID-19 infection among T2DM patients. This study detected that 25% of patients with COVID-19 and T2DM experienced mental distress, with sleeping disturbances and lifestyle changes markedly impacting their clinical outcome alongside metabolic and serum parameters.