Emerging evidence has indicated a possible link between obesity in early life with subsequent cancer risks, but its association with gastric cancer remains unknown. This study aimed to investigate the association of obesity at ages 18–20 and 35 with the later risk of gastric cancer among the Korean population. Included were 122,724 individuals who participated in the large-scale prospective cohort study, the Health Examinees-Gem (HEXA-G) study, during 2004–2017. Multivariable Cox proportional hazards models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for gastric cancer risk associated with body mass index (BMI) at ages 18–20 and 35 years. During a mean follow-up period of 8.6±2.1 years, a total 927 gastric cancer cases (531 men and 396 women) were identified. When compared to normal BMI (18.5–23.0 kg/m2), obesity (BMI ≥30 kg/m2) at age 35 was significantly associated with increased risk of gastric cancer later in life among total participants (HR 1.94, 95% CI 1.26–2.97, p 0.01). When analyzed separately by sex, obesity at 35 years of age was significantly associated with increased risk of gastric cancer among both men (HR 1.79, 95% CI 1.02–3.13, p 0.05) and women (HR 2.35, 95% CI 1.21–4.60, p 0.02). No significant associations were found for obesity at late adolescence in both men and women. Our findings suggest that obesity in early adulthood may be associated with an increased risk of gastric cancer. The results may aid in understanding the etiology of GC in a population with a divergent trend of gastric cancer.

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Objective: Epidemiological studies indicate that alcohol increases gastric cancer (GC) risk, yet most studies have focused on heavy alcohol intake, leaving other factors understudied. A comprehensive investigation of the effects of the frequency and amount of alcohol intake may help elucidate the GC risk associated with drinking behavior. Methods: The Health Examinees-Gem (HEXA-G) study, a community-based large-scale prospective cohort study, enrolled Korean adults 40–69 years of age between the years 2004 and 2013. Incident GC cases were identified through linkage to Korea Central Cancer Registry data until December 31, 2017. Self-reported questionnaires were used to survey alcohol consumption-related factors (duration, frequency, amount, and type of alcoholic beverages). The frequency and amount of alcohol consumption were combined to explore GC risk according to 4 drinking patterns: “infrequent-light”, “frequent-light”, “infrequent-heavy”, and “frequent-heavy”. We used Cox proportional hazard models to estimate the adjusted hazard ratios (HRs) and 95% confidence intervals (CIs), and investigate the relationship between alcohol intake and GC incidence. Results: A total of 128,218 participants were included in the analysis. During an average follow-up period of 8.6 years, 462 men and 385 women were diagnosed with GC. In men, current drinkers showed a 31% greater risk of GC than non-drinkers (HR 1.31, 95% CI 1.03–1.66), whereas no significant association was observed in women. In men, GC risk was associated with a higher frequency (P trend 0.02) and dose of ethanol intake in grams (P trend 0.03). In men, the “frequent-light” (≥5 times/week and <40 g ethanol/day) drinking pattern was associated with a 46% greater risk of GC (HR 1.46, 95% CI 1.02–2.07) than the “infrequent-light” pattern (<5 times/week and <40 g ethanol/day). Conclusions: This study suggests that frequent intake of alcohol, even in low quantities per session, increases GC risk. Further research is warranted to evaluate the relationship between alcohol and GC in detail.

With increases in life expectancy, the focus has shifted to living a healthier, longer life. By concentrating on preventing diseases before occurrence, researchers aim to diminish the increasing gap in medical costs and health inequalities prevalent across many nations. Although we have entered an era of post-genomics, we are still in infancy in terms of personalized preventive research. Personalized preventive research has and will continue to improve with advancements in the use of biomarkers and risk assessment. More evidence based on well-designed epidemiologic studies is required to provide comprehensive preventive medical care based on genetic and non-genetic profile data. The realization of personalized preventive research requires building of evidence through appropriate methodology, verification of results through translational studies as well as development and application of prediction models.