Life satisfaction and mortality in elderly people: The Kangwha Cohort Study

<p>Abstract</p> <p>Background</p> <p>As well as biomedical risk factors, psychological factors have been reported to be related to mortality rate. The purpose of this study was to examine the relationship between life satisfaction and mortality in elderly people through an 11.8-year follow-up study of a prospective cohort.</p> <p>Methods</p> <p>Among 3,600 participants of the Kangwha Cohort Study who survived in 1994, 1,939 respondents of the Life Satisfaction Index (LSI)-A questionnaire were included (men, 821; women, 1118). The mortality risk for the period up to December 2005 was measured using the Cox Proportional Hazard Model.</p> <p>Results</p> <p>When the relationship between LSI and mortality was evaluated in men, the unsatisfied group with lower LSI scores showed a significantly higher risk of all-cause mortality (hazard ratio [HR], 1.42; 95% confidence interval [CI], 1.11-1.83) than the satisfied group with higher LSI scores. In women, the unsatisfied group showed a significantly higher risk of all-cause mortality (HR, 1.51; 95% CI, 1.18-1.92) and cardiovascular mortality (HR, 2.23; 95% CI, 1.30-3.85) than the satisfied group.</p> <p>Conclusion</p> <p>We found that elderly people with a lower LSI score, regardless of gender, were at risk of increased mortality from all causes, and low LSI score was also associated with cardiovascular mortality.</p

Investigation of circulating metabolites associated with breast cancer risk by untargeted metabolomics: a case–control study nested within the French E3N cohort

BACKGROUND: Perturbations in circulating metabolites prior to a breast cancer diagnosis are not well characterised. We aimed to gain more detailed knowledge to help understand and prevent the disease. METHODS: Baseline plasma samples from 791 breast cancer cases and 791 matched controls from the E3N (EPIC-France) cohort were profiled by nuclear magnetic resonance (NMR)-based untargeted metabolomics. Partial least-squares discriminant analysis (PLS-DA) models were built from NMR profiles to predict disease outcome, and odds ratios and false discovery rate (FDR)-adjusted CIs were calculated for 43 identified metabolites by conditional logistic regression. RESULTS: Breast cancer onset was predicted in the premenopausal subgroup with modest accuracy (AUC 0.61, 95% CI: 0.49-0.73), and 10 metabolites associated with risk, particularly histidine (OR = 1.70 per SD increase, FDR-adjusted CI 1.19-2.41), N-acetyl glycoproteins (OR = 1.53, FDR-adjusted CI 1.18-1.97), glycerol (OR = 1.55, FDR-adjusted CI 1.11-2.18) and ethanol (OR = 1.44, FDR-adjusted CI 1.05-1.97). No predictive capacity or significant metabolites were found overall or for postmenopausal women. CONCLUSIONS: Perturbed metabolism compared to controls was observed in premenopausal but not postmenopausal cases. Histidine and NAC have known involvement in inflammatory pathways, and the robust association of ethanol with risk suggests the involvement of alcohol intake