Socioeconomic disparities in gastric cancer and identification of a single SES variable for predicting risk
| Autor: | Marc J. Dauer, Srawani Sarkar, Haejin In |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
business.industry
Gastroenterology Survey research Logistic regression Article 03 medical and health sciences Variable (computer science) 0302 clinical medicine Increased risk Oncology Social Class Socioeconomic Factors Single indicator Risk Factors Stomach Neoplasms 030220 oncology & carcinogenesis Income Household income Medicine Humans 030211 gastroenterology & hepatology Risk factor business Socioeconomic status Demography |
| Zdroj: | J Gastrointest Cancer |
| Popis: | INTRODUCTION: Socioeconomic status (SES) is a known risk factor for gastric cancer (GC). This study seeks to examine education, income, and occupation variables separately to identify the single variable that can be best used to assess SES risk for GC. METHODS: Data from a case-control survey study were used. Logistic regression models were created for education, income, and occupation adjusted for age, sex, and race. Models were compared using AIC, c-statistics, and pseudo-R square to determine the model that had the highest risk predictive ability. RESULTS: GC cases had lower education levels, and more commonly held jobs in unskilled labor. Annual household income was lower in cases compared to controls. Age, gender, race, education and occupation were associated with increased risk of GC. The education model adjusted for age, gender, and race found HS education. The occupation model demonstrated that employment in unskilled labor had OR of 4.32 (95% CI 1.05–17.76) for GC compared to professional occupation. Model fit was best for the education model (AIC: 113.583, lower AIC is better) compared to income (117.562) or occupation (117.032). Education contributed the most to model variability [% delta-pseudo-R square (4.7%)] compared to occupation (4.0%) or income (3.8%). CONCLUSION: Education level was the single most reliable measure of GC risk among 3 SES variables and can be employed as an ideal single indicator of SES related GC risk when multiple SES factors cannot be obtained. |
| Databáze: | OpenAIRE |
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