The Influence of Family History Risk Levels of Diabetes on Disease Prevalence in a High-Risk Diabetic Chinese Population.


BACKGROUND Diabetes is associated with genetic susceptibility, and family history is a risk factor. The study investigated the association between different family history risk levels and the prevalence of diabetes in a multi high-risk cohort and evaluated the impact of family history of diabetes on insulin secretion and insulin sensitivity. MATERIALS AND METHODS We analyzed data from 9754 adults who participated in the Shanghai High-Risk Diabetic Screen Project between 2002 and 2012. The association among three family history risk levels (mild, moderate, and high) with the prevalence of diabetes, insulin secretion, and insulin sensitivity was evaluated in the multi high-risk cohort. RESULTS Overall, 69.6%, 24.8%, and 5.6% of participants were categorized as having mild, moderate, and high familial risk, respectively. The standardized prevalence was higher in the high family history risk group (43.1%) than in the moderate group (37.3%) and in the mild group (23.5%) (P < 0.001). The odds ratios (ORs) were significantly increased in the moderate group (OR 1.27, 95% confidence interval [CI] 1.15-1.40, P < 0.05) and in the high group (OR 1.69, 95% CI 1.41-2.02, P < 0.05). Among the 3245 normal glucose tolerance participants, insulin secretion significantly declined with increasing levels of family history risk, but there were no significant differences in insulin sensitivity among the three groups. CONCLUSION The prevalence of diabetes was independently associated with an increasing family history risk level among multi high-risk Chinese populations. Subjects with moderate and high familial history of diabetes displayed a significant decrease in insulin secretion.

DOI: 10.1089/dia.2016.0023

Cite this paper

@article{Du2016TheIO, title={The Influence of Family History Risk Levels of Diabetes on Disease Prevalence in a High-Risk Diabetic Chinese Population.}, author={Xiujuan Du and Yinan Zhang and Fei Gao and Huijuan Lu and Yixie Shen and Ruihua Chen and Pingyan Fang and Yuqian Bao and Congrong Wang and Weiping Jia}, journal={Diabetes technology & therapeutics}, year={2016}, volume={18 8}, pages={494-8} }