C-peptide is usually considered as a marker of insulin secretion and has no physiological function. This study aimed to assess the association between serum C-peptide level as independent risk factor and breast cancer and explored the possible underlying mechanisms. This was a population-based cohort study. All the data was collected according to a standard protocol. The C-peptide and insulin-like growth factor binding proteins-3(IGFBP-3) concentrations were measured in blood. The breast cancer deaths were confirmed by National Death Index records. Cox proportional hazard regression analysis was conducted to determine the hazard ratio of serum C-peptide level for breast cancer deaths. Analysis of covariance was used to assess the association between serum C-peptide and IGFBP-3 level, and the linear trend was tested by using a linear model. A total of 8,373 women 17 years of age or older were included in the study, and 57 breast cancer deaths were observed over the study period. The result of survival analysis showed that breast cancer deaths increased with increasing levels of serum C-peptide. The hazard ratio was 1.69 (95% confidence interval, 1.17–2.45). The levels of circulating IGFBP-3 were positively associated with changes in serum C-peptide levels and showed a strong linear trend in the covariance analysis. Serum C-peptide level was associated with increased risk of breast cancer death. Our results suggest that the increased risk of breast cancer death can be via a pathway that serum C-peptide level positive associated with the change in serum IGFBP-3 level.

BackgroundDependence is a common mental disorder among the elderly increases with increasing age，and can lead to serious health problems. This study aimed to assess the association between social resources and dependency, and explored the effect of social support on modification of important risk factors for dependency among elderly.Method The present study was a population-based cross-sectional study. A total of 950 participants aged ≥ 60 years were selected using a complex multistage sampling design from 22 locations in China. All data were collected using questionnaires by face-to-face interviews. The dependency was assessed using the standardized Minnesota Multiphasic Personality Inventory-II, and the social resource was assessed using the questionnaires of Older American Resources and Services (OARS) in Chinese version. The logistic regression analysis was used to evaluate the association between dependency and social resources. The analysis of covariance was performed to evaluate the effect of social support on modification of important risk factors for dependency.ResultsA total of 913 participants were included in the analysis, and 10.3% of males and 14.4% of females were identified as dependency. The results of logistic regression analysis showed that a significant negative association between the levels of social resource and dependency. The odds ratio was 0.78 (95% CI, 0.73–0.84) after adjusting for important confounding factors. The results of analysis of covariance showed the differences in the mean dependency score between different chronic disease status and social support level.ConclusionThe levels of social resources were negatively associated with dependency. Our results suggest that the social support had both a direct effect on dependency and an indirect effect through modifying chronic disease status and individual income.