The status and risk factors for anxiety/depression in patients with atrophic chronic gastritis: a cross-sectional study.

BACKGROUND

Atrophic chronic gastritis (ACG) is a preneoplastic condition of gastric carcinoma. Numerous studies have shown anxiety and depression can affect gastrointestinal function, which may promote gastrointestinal disorders development and progression. Thus, we hypothesized that anxiety and depression may enhance the development and progression of ACG. In this study, we aimed to analyse risk factors for anxiety and depression in ACG patients and integrate these risk factors to construct an effective clinical prediction model.

METHODS

In total, 118 ACG patients were included from July 2021 to May 2022. Anxiety and depression were assessed utilizing the Generalized Anxiety Disorder-7 (GAD-7) and Patient Health Questionnaire-9 (PHQ-9). Data were collected on demographic characteristics, lifestyle, and dietary habits. Risk factors for anxiety and depression were explored with univariate analysis and multivariate stepwise logistic regression, and risk prediction models were built.

RESULTS

Among 118 ACG patients, 36.4% had anxiety, 25.4% had depression, and 21.2% had both anxiety and depression. Poor sleep quality [odd ratio (OR) 4.32, 95% confidence interval (CI): 1.60-11.65, P=0.004] was positively associated with risk of anxiety, while smoking (OR 0.15, 95% CI: 0.03-0.68, P=0.014) and weekly exercise time (OR 0.89, 95% CI: 0.79-0.99, P=0.037) were negatively associated with risk of anxiety. The area under the receiver operating characteristic (ROC) curve was 80.3%, 95% CI: [0.722-0.885]. The sensitivity was 72.1%, and the specificity was 78.7%. Poor sleep quality (P<0.001, OR 23.89, 95% CI: 4.05-141.05), high salt diet (P=0.004, OR 6.94, 95% CI: 1.86-25.96), family history of tumours (P=0.020, OR 6.10, 95% CI: 1.33-27.93), and abdominal pain (P=0.018, OR 4.44, 95% CI: 1.29-15.23) were positively associated with the risk of depression, with an area under the ROC curve of 77.3%, 95% CI: 0.687-0.860. The sensitivity was 83.3%, and the specificity was 62.5%.

CONCLUSIONS

Potential anxiety and depression in ACG patients can be identified early by referring to risk factors and protective factors. The prediction model could be used to detect anxiety and depression in ACG patients at their earliest stage and provide meaningful suggestions for ACG patients.