ABSTRACT
BACKGROUND: While multiple studies have evaluated the effect of body mass index (BMI) on the prevalence of gastrointestinal (GI) symptoms, data from Saudi Arabia are scarce. This study aimed to evaluate the association between GI symptoms and BMI in a Saudi population. METHODS: A prospective cross-sectional study was conducted between September 2019 and April 2020. The data were collected using an electronic self-administered questionnaire. The study included adult participants and collected data on patients' demographics and GI symptoms. Participants with underlying GI diseases were excluded. A multivariate regression analysis was used to report the adjusted prevalence of GI symptoms in different BMI categories. RESULTS: A total of 4415 participants completed the survey. After applying the exclusion criteria, 3866 were included. The mean age was 26.3 (±8.8) and 58.2% were females. The mean BMI was 25.2 (±6.7), and the distribution of BMI was as follows: underweight 428 (11.1%), normal BMI 1789 (46.2%), overweight 912 (23.5%), and obese 737 (19.1%). After adjustment for age, gender, and smoking and coffee habits, obesity (BMI > 30) was significantly associated with heartburn (p < 0.01, aOR 1.6, 95% CI: 1.33 - 1.92), bloating (p < 0.01, aOR 1.31, 95% CI: 1.08 - 1.6), and diarrhea (p < 0.01, aOR 1.72, 95% CI: 1.36 - 2.17)). Underweight (BMI < 18.5) was significantly associated with abdominal pain (p < 0.01, aOR 1.4, 95% CI: 1.12 - 1.73), nausea (p < 0.01, aOR 1.6, 95% CI: 1.29 - 2.1), and vomiting (p < 0.01, aOR 2.02, 95% CI: 1.23 - 3.25). There was no significant association between BMI and constipation. CONCLUSION: Obesity was associated with heartburn, diarrhea, and bloating, while underweight status was associated with nausea, vomiting, and abdominal pain. No association between BMI and constipation was found.
ABSTRACT
Introduction: Salmonella infection is one of the most common causes of gastroenteritis worldwide. It is associated with high morbidity and mortality if not treated properly. It has developed resistance to multiple antibiotics. These developments are concerning. This study sought to observe common patterns of invasive Salmonella infections, such as the common serotypes involved, presentation, sensitive investigations, and effective treatment. This study also aimed to examine the risk factors that can worsen the infection and increase morbidity and mortality. Methodology: This retrospective analysis included all patients who were diagnosed with invasive Salmonella infection at King Khalid University Hospital from May 2017 to December 2018. Most patients in this report were immunocompromised; however, a few previously healthy patients. Different types of specimens were collected. Twenty-two patients with invasive Salmonella were included in this study. Results: Sixteen of them had underlying conditions. The most common presenting symptoms of illness were fever (n = 13), vomiting (n = 6), and diarrhea (n = 4). Most blood samples (94%) were positive for Salmonella. All patients were discharged except three who died; these were all older patients with comorbidities. Although four different antimicrobial resistance patterns were noticed in this study, ciprofloxacin was the highest significant percentage (62.5%). Of five patients initially treated with ciprofloxacin, three of them expressed resistance to this antibiotic. Conclusion: The findings of this study support that immunocompromised patients and people with extreme ages are more likely to have serious medical illnesses and at higher risk of infection with Salmonella spp. Therefore, this study emphasises the importance of antimicrobial judicious utilisation. Tackling the escalating antibiotic resistance could be approached by implementing advanced public education levels to maintain high standards of food and water safety. Moreover, the urge to investigating newer drugs against Salmonella with an acceptable safety profile is a cornerstone to attenuate the rapidly acquired bacterial resistance precisely for those who are immunocompromised. Furthermore, predicting the mortality, morbidity and the clinical response is feasible according to the patient parameters and comorbidities.
