Body Mass Index and Helicobacter pylori among Obese and Non-Obese Patients in Najran, Saudi Arabia: A Case-Control Study.
Ali M Al-ZubaidiAbdo H AlzobydiSaeed A AlsareiiAbdulazizTurky Al-ShahraniNaweed AlzamanSaba Abdulla KassimPublished in: International journal of environmental research and public health (2018)
Objective: We examine obese and non-obese patients with respect to Helicobacter pylori (H. pylori) positive-infection (HPPI) and associated factors, specifically body mass index (BMI). Methods: This study took place in the Department of Endoscopy of a central hospital in the Najran region of Saudi Arabia (SA). A total of 340 obese Saudi patients (BMI ≥ 30 kg/m²) who had undergone diagnostic upper endoscopy before sleeve gastrectomy, were compared with 340 age and gender-matched control patients (BMI < 30 kg/m²) who had undergone diagnostic upper endoscopy for other reasons. Data collected included diagnosis of HPPI. Descriptive and multivariable binary logistic regression was conducted. Results: Mean patient age was 31.22 ± 8.10 years, and 65% were males. The total prevalence of HPPI was 58% (95% CI = 54⁻61%) with obese patients presenting significantly more HPPI than non-obese patients (66% vs. 50%, OR = 1.98, 95% CI = 1.45⁻2.70, p < 0.0005). Age and gender did not associate significantly with HPPI (p = 0.659, 0.200, respectively) and increases in BMI associated significantly with increases in HPPI (p < 0.0005). BMI remained a significant factor in HPPI when modelled with both age and gender (OR = 1.022, 95% CI = 1.01⁻1.03, p < 0.0005). Conclusions: Within the limitations of this study, the significance of HPPI in obese Saudi patients residing in the Najran region in SA was demonstrated alongside the significance role of BMI in HPPI.
Keyphrases
- obese patients
- body mass index
- helicobacter pylori
- bariatric surgery
- saudi arabia
- gastric bypass
- end stage renal disease
- weight loss
- roux en y gastric bypass
- adipose tissue
- type diabetes
- ejection fraction
- newly diagnosed
- weight gain
- metabolic syndrome
- chronic kidney disease
- prognostic factors
- healthcare
- peritoneal dialysis
- machine learning
- physical activity
- artificial intelligence
- ionic liquid
- small bowel
- big data
- tertiary care