In observational studies, identifying and adjusting for a sufficient set of confounders is crucial for accurately estimating the causal effect of the exposure on the outcome. Even in studies with large sample sizes, which typically benefit from small variances in estimates, there is a risk of producing estimates that are precisely inaccurate if the study suffers from systematic errors or biases, including confounding bias. To date, several approaches have been developed for selecting confounders. In this article, we first summarize the epidemiological and statistical approaches to identifying a sufficient set of confounders. Particularly, we introduce the modified disjunctive cause criterion as one of the most useful approaches, which involves controlling for any pre-exposure covariate that affects the exposure, outcome, or both. It then excludes instrumental variables but includes proxies for the shared common cause of exposure and outcome. Statistical confounder selection is also useful when dealing with a large number of covariates, even in studies with small sample sizes. After introducing several approaches, we discuss some pitfalls and considerations in confounder selection, such as the adjustment for instrumental variables, intermediate variables, and baseline outcome variables. Lastly, as it is often difficult to comprehensively measure key confounders, we introduce two statistics, E-value and robustness value, for assessing sensitivity to unmeasured confounders. Illustrated examples are provided using the National Health and Nutritional Examination Survey Epidemiologic Follow-up Study. Integrating these principles and approaches will enhance our understanding of confounder selection and facilitate better reporting and interpretation of future epidemiological studies.

Background: Instrumental variable (IV) methods are widely employed to estimate causal effects when concerns regarding unmeasured confounders. Although comparisons among several IV methods for binary outcomes exist, comprehensive evaluations are insufficient. Therefore, in this study, we aimed to conduct a simulation with some settings for a detailed comparison of these methods, focusing on scenarios where IVs are valid and under effect homogeneity with different instrument strengths.

Methods: We compared six IV methods under 32 simulation scenarios: two-stage least squares (2SLS), two-stage predictor substitutions (2SPS), two-stage residual inclusions (2SRI), limited information maximum likelihood (LIML), inverse-variance weighted methods with a linear outcome model (IVW_LI), and inverse-variance weighted methods with a non-linear model (IVW_LL). By comparing these methods, we examined three key estimates: the parameter estimates of the exposure variable, the causal risk ratio, and the causal risk differences.

Results: Based on the results, six IV methods could be classified into three groups: 2SLS and IVW_LI, 2SRI and 2SPS, and LIML and IVW_LL. The first pair showed a clear bias owing to outcome model misspecification. The second pair showed a relatively good performance when strong IVs are available; however, the estimates suffered from a significant bias when only weak IVs are used. The third pair produced relatively conservative results, although they were less affected by weak IV issues.

Conclusion: The findings indicate that no panacea is available for the bias associated with IV methods. We suggest using multiple IV methods: one for primary analysis and another for sensitivity analysis.

Background: Hepatitis C virus (HCV) infection is a systemic disease. However, the relative contribution of intrahepatic and extrahepatic diseases to mediating HCV-induced mortality is unclear, albeit critical in resource allocation for reducing preventable deaths. To this end, this study comprehensively quantified the extent to which intrahepatic and extrahepatic diseases mediate HCV-induced mortality.

Methods: A community-based cohort study with >25 years of follow-up was conducted in Taiwan. HCV infection was profiled by antibodies against HCV and HCV RNA in participants’ serum samples. The cohort data were linked to Taiwan’s National Health Insurance Research Database to determine the incidences of potential mediating diseases and mortality. We employed causal mediation analyses to estimate the mediation effects of HCV on mortality in relation to the incidences of 34 candidate diseases.

Results: In 18,972 participants with 934 HCV infection, we observed that 54.1% of HCV-induced mortality was mediated by intrahepatic diseases, such as liver cirrhosis and liver cancer, and 45.9% of mortality was mediated by extrahepatic diseases. The major extrahepatic mediating diseases included septicemia (estimated proportion of HCV-induced mortality mediated through the disease: 25.2%), renal disease (16.7%), blood/immune diseases (12.2%), gallbladder diseases (9.7%), and endocrine diseases (9.6%). In women, hypertension (20.0%), metabolic syndrome (18.9%), and type 2 diabetes (17.0%) also mediated HCV-induced mortality. A dose-response relationship of HCV viral load was further demonstrated for the mediation effect.

Conclusion: Both intrahepatic and extrahepatic manifestations mediated approximately half of HCV-induced mortality. The mediation mechanisms are supported by a dose-response relationship of HCV viral load.

Background: Individuals with type 2 diabetes mellitus (T2DM) have increased colorectal cancer (CRC) risk, but it is unknown whether income dynamics are associated with CRC risk in these individuals. We examined whether persistent low- or high-income and income changes are associated with CRC risk in non-elderly adults with T2DM.

Methods: Using nationally representative data from the Korean Health Insurance Service database, 1,909,492 adults aged 30 to 64 years with T2DM and no history of cancer were included between 2009 and 2012 (median follow-up of 7.8 years). We determined income levels based on health insurance premiums and assessed annual income quartiles for the baseline year and the four preceding years. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated after adjusting for sociodemographic factors, CRC risk factors, and diabetes duration and treatment.

Results: Persistent low income (ie, lowest income quartile) was associated with increased CRC risk (HR_{5 years vs 0 years} 1.11; 95% CI, 1.04–1.18; P for trend = 0.004). Income declines (ie, a decrease ≥25% in income quantile) were also associated with increased CRC risk (HR_{≥2 vs 0 declines} 1.10; 95% CI, 1.05–1.16; P for trend = 0.001). In contrast, persistent high income (ie, highest income quartile) was associated with decreased CRC risk (HR_{5 years vs 0 years} 0.81; 95% CI, 0.73–0.89; P for trend < 0.0001), which was more pronounced for rectal cancer (HR 0.64; 95% CI, 0.53–0.78) and distal colon cancer (HR 0.70; 95% CI, 0.57–0.86).

Conclusion: Our findings underscore the need for increased public policy awareness of the association between income dynamics and CRC risk in adults with T2DM.

Background: Dementia is the leading cause of disability and imposes a significant burden on society. Previous studies have suggested an association between metabolites and cognitive decline. Although the metabolite composition differs between Western and Asian populations, studies targeting Asian populations remain scarce.

Methods: This cross-sectional study used data from a cohort survey of community-dwelling older adults aged ≥60 years living in Miyagi, Japan, conducted by Tohoku Medical Megabank Organization between 2013 and 2016. Forty-three metabolite variables quantified using nuclear magnetic resonance spectroscopy were used as explanatory variables. Dependent variable was the presence of cognitive decline (≤23 points), assessed by the Mini-Mental State Examination. Principal component (PC) analysis was performed to reduce the dimensionality of metabolite variables, followed by logistic regression analysis to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for cognitive decline.

Results: A total of 2,940 participants were included (men: 49.0%, mean age: 67.6 years). Among them, 1.9% showed cognitive decline. The first 12 PC components (PC1–PC12) accounted for 71.7% of the total variance. Multivariate analysis showed that PC1, which mainly represented essential amino acids, was associated with lower odds of cognitive decline (OR 0.89; 95% CI, 0.80–0.98). PC2, which mainly included ketone bodies, was associated with cognitive decline (OR 1.29; 95% CI, 1.11–1.51). PC3, which included amino acids, was associated with lower odds of cognitive decline (OR 0.81; 95% CI, 0.66–0.99).

Conclusion: Amino acids are protectively associated with cognitive decline, whereas ketone metabolites are associated with higher odds of cognitive decline.

Background: The participation rate for screening is regarded as a useful indicator for preventing cancer and cardio-metabolic disease. However, the validity of self-reported screening participation has not yet been thoroughly evaluated in Japan. We aimed to examine its validity using the municipal screening records among the Japanese population.

Methods: We included 3,060 men and 3,860 women insured by the National Health Insurance for residents aged <75 years or the Medical Care System for the Elderly aged ≥75 years in the Chikusei area of the Japan Public Health Center-based Prospective Study for the Next Generation. They were asked about their participation in cancer screenings and health checkups during the previous year. We compared their responses to the municipal records and calculated the sensitivity and specificity of self-reported screening participation.

Results: The sensitivity and specificity of self-reported participation were 0.49 and 0.86 for lung cancer screening, 0.67 and 0.85 for colorectal cancer screening, 0.77 and 0.79 for stomach cancer screening, and 0.86 and 0.65 for health checkup, respectively. Among women, the sensitivity and specificity were 0.83 and 0.81 for breast cancer and 0.85 and 0.90 for cervical cancer, respectively.

Conclusion: Self-reported cancer screening participation for colorectal, stomach, breast, and cervical cancers had moderate-to-high sensitivity and specificity. Self-reported participation, especially for lung cancer screening and health checkups, should be carefully interpreted when assessing the performance of preventive measures.