Investigating the Factors Related to Gastric Cancer with Conditional Logistic Regression Model: A Cross-Sectional-Retrospective Study

AuthorArmin Naghipour
AuthorAbbass Moghimbeigi
AuthorJalal Poorolajal
AuthorAbdolazim Sadighi-Pashaki
Issued Date2023-03-31
AbstractBackground: The incidence of stomach cancer in Iran, especially in the western and northwestern regions, has increased in recent years. Objectives: This study aimed to report the identified factors related to stomach cancer in Hamadan province. Methods: In this retrospective descriptive study, the data were collected by a researcher-made checklist. The 1: 2 matched controls were considered for each patient. Controls were age (± 5 years) and sex-matched. The control group was selected from a hospital sample with and without a family history of cancer. The data analysis was analyzed using a conditional logistic regression model under Stata software. Results: A total of 100 patients (male n = 77 and female n = 23) with gastric cancer (cases) were studied. The results showed that many variables such as smoking (P < 0.05), blood type (P < 0.05), job (P < 0.05), red meat (P < 0.05), pickle (P < 0.05), hot food (P < 0.05), salt (P < 0.05), alcohol (P < 0.05), and black tea (P < 0.05) were risk factors and variables such as education (P < 0.05), vegetables (P < 0.05), fruit (P < 0.05), fish (P < 0.05), physical activity (P < 0.05), broccoli (P < 0.05), and garlic (P < 0.05) were the preventive factors for gastric cancer. There was no difference between the investigated factors of controls with a family history of cancer and those without one. Conclusions: Health and treatment organizations and health policymakers are expected to reduce the incidence of stomach cancer by raising awareness and promoting proper diet by reporting the preventive and risk factors.
DOIhttps://doi.org/10.5812/jkums-133834
KeywordGastric Cancer
KeywordStomach Cancer
KeywordRisk Factor
KeywordFamily History
KeywordNutrition Status
PublisherBrieflands
TitleInvestigating the Factors Related to Gastric Cancer with Conditional Logistic Regression Model: A Cross-Sectional-Retrospective Study
TypeResearch Article
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