Abstract

Abstract Objectives Excessive dietary iron intake may lead to iron overload and further induce pancreatic islet damage to increase risk of diabetes, which has a higher prevalence in middle-aged and elderly population. We aimed to explore the association between dietary iron intake and incident type 2 diabetes (T2D) in Chinese middle-aged and elderly population. Methods This study was based on the Guangzhou Nutrition and Health Study (GNHS), an on-going, community-based prospective cohort study that recruited participants aged 40–75 years from 2008. All participants were followed up every three years. 2765 participants free of diabetes were included in data analysis. Dietary iron intake was obtained by a validated food-frequency questionnaire at baseline. T2D was ascertained by self-reported diabetes medications, fasting glucose ≥7.0 mmol/L or glycosylated hemoglobin ≥6.5%. Cox proportional hazards models were used to estimate HRs and 95% CIs. Results We ascertained 209 incident diabetes cases during 13,634 person-years of observation. The mean ± SD intakes of dietary total iron, heme iron and nonheme iron among all participants were 20.40 ± 2.73 mg/d, 1.26 ± 0.62 mg/d and 19.14 ± 2.66 mg/d, respectively. The multivariate-adjusted HR and 95% CI for T2D for the highest quartile of heme iron intake compared with the lowest quartile was 2.11 (95% CI: 1.14–3.89, P-trend = 0.014). However, the association between total iron intake or a nonheme iron intake with T2D risk was no significant difference. The adjusted HR for T2D risk was 1.79 (95% CI:1.05–3.08, P-trend = 0.037) for heme iron intake from red meat, while no association was found for heme iron intake from poultry or fish. Conclusions Greater intake of heme iron, especially heme iron from red meat, was associated with higher risk of incident T2D in Chinese middle-aged and elderly population, while intakes of total iron and nonheme were not related to diabetes. Controlling heme iron intake, especially red meat intake, may be a target to prevent T2D in middle-aged and elderly population. Funding Sources The National Science Foundation of China; the National Science Foundation of Guangdong Province, China.

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