Analiz Riska Zdorovʹû (Dec 2019)

Correlation between atrophic gastritis and risk factors prevalence among workers employed at atomic enterprise

  • E.I. Rabinovich,
  • V.F. Obesnyuk,
  • S.V. Povolotskaya,
  • S.N. Sokolova,
  • M.A. Vasina,
  • S.S. Sokol'nikova

DOI
https://doi.org/10.21668/health.risk/2019.4.11.eng
Journal volume & issue
no. 4
pp. 104 – 112

Abstract

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Atrophy of the mucous tunic in the stomach is a significant predisposing factor that causes elevated risks of stomach adenocarcinoma. It was shown that mortality caused by malignant neoplasms in the digestive organs accounted for 36 % of all the death cases due to solid carcinoma among workers employed at basic enterprises included into “Mayak” Production Associa-tion (Mayak PA). Our research goal was to examine a correlation between atrophic gastritis (AG) prevalence and potentially hazardous endogenous and exogenous factors among personnel employed at an atomic enterprise of Mayak PA. We analyzed data obtained via clinical and laboratory examinations performed on a sampling that was made of 1.116 people, 70 % of them being workers employed at Mayak PA. Our research allowed us to reveal and analyze 26 hazardous factors that contributed to AG development. Data array was processed with a modified “case – control” procedure based on well-known principal components analysis. Observation clusters and strata that formed certain groups in various areas of the factor space differed both as per “overloading” with risk factors and as per intensity of an effect. Accomplished analysis allowed us to conclude that there was a correlation between AG development and risk factors prevalence as we revealed certain factors exerting statistically significant impacts on AG develop-ment in the examined sampling even within the zero hypotheses H0. In order to determine how intense that correlation was, in further analysis it was advisable to apply an alternative hypothesis H1 on a possible correlation between an effect and examined factors. Application of a modified statistical procedure allowed us to make any conclusions only on certain trends occurring in AG risks when there were some changes in aggregated overloading with risk factors; adequate and complete statistical analysis can only be multi-factor one. As “factor – effects” correlations lack evidence, it creates a possibility for neuronet approximations; we are going to demonstrate it in our future works.

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