Cluster of lifestyle risk factors for stomach cancer and screening behaviors among Korean adults

Disparities in Cancer Mortality among Disaggregated Asian American Subpopulations, 2018-2021

Federal, state, and institutional data collection practices and analyses involving Asian Americans as a single, aggregated group obscure critical health disparities among the vast diversity of Asian American subpopulations. Using from the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) Underlying Causes of Death database, we conducted a cross-sectional study using data on disaggregated Asian American subgroups (Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese, other Asians) between 2018 and 2021. We examine deaths from 22 cancer types and in situ, benign neoplasms, identified using ICD-10 codes C00-C97 and D00-D48. Overall, our study comprised 327,311 Asian American decedents, with a mean age of death at 70.57 years (SD=2.79), wherein females accounted for approximately half of the sample (n=36,596/73,207; 49.99%). Notably, compared to the aggregated Asian American reference group, we found higher proportions of deaths from total cancers among Chinese (25.99% vs. 22.37% [ref]), Korean (25.29% vs. 22.37% [ref]), and Vietnamese (24.98% vs. 22.37% [ref]) subgroups. In contrast, total cancer deaths were less prevalent among Asian Indians (17.49% vs. 22.37% [ref]), Japanese (18.90% vs. 22.37% [ref]), and other Asians (20.37% vs. 22.37% [ref]). We identified further disparities by cancer type, sex, and age. Disaggregated data collection and analyses are imperative to understanding differences in cancer mortality among Asian American subgroups, illustrating at-risk populations with greater granularity. Future studies should aim to describe the association between these trends and social, demographic, and environmental risk factors.

Development of a gastric cancer risk calculator for questionnaire-based surveillance of Iranian dyspeptic patients

BACKGROUND

Gastric cancer (GC) is considered a silent killer, taking more than three quarters of a million lives annually. Therefore, prior to further costly and invasive diagnostic approaches, an initial GC risk screening is desperately in demand.

METHODS

In order to develop a simple risk scoring system, the demographic and lifestyle indices from 858 GC and 1132 non-ulcer dyspeptic (NUD) patients were analysed. We applied a multivariate logistic regression approach to identify the association between our target predictors and GC versus NUD. The model performance in classification was assessed by receiver operating characteristic (ROC) analysis. Our questionnaire covering 64 predictors, included known risk factors, such as demographic features, dietary habits, self-reported medical status, narcotics use, and SES indicators.

RESULTS

Our model segregated GC from NUD patients with the sensitivity, specificity, and accuracy rates of 85.89, 63.9, and 73.03%, respectively, which was confirmed in the development dataset (AUC equal to 86.37%, P < 0.0001). Predictors which contributed most to our GC risk calculator, based on risk scores (RS) and shared percentages (SP), included: 1) older age group [> 70 (RS:+ 241, SP:7.23), 60-70 (RS:+ 221, SP:6.60), 50-60 (RS:+ 134, SP:4.02), 2) history of gastrointestinal cancers (RS:+ 173, SP:5.19), 3) male gender (RS:+ 119, SP:3.55), 4) non-Fars ethnicity (RS:+ 89, SP:2.66), 5) illiteracy of both parents (RS:+ 78, SP:2.38), 6) rural residence (RS:+ 77, SP:2.3), and modifiable dietary behaviors (RS:+ 32 to + 53, SP:0.96 to 1.58).

CONCLUSION

Our developed risk calculator provides a primary screening step, prior to the subsequent costly and invasive measures. Furthermore, public awareness regarding modifiable risk predictors may encourage and promote lifestyle adjustments and healthy behaviours.