<p>Previous studies have linked single metal with diabetic retinopathy (DR), but information about the combined effects of multiple metals mixture was scarce. Thus, we performed this cross-sectional study to investigate the single and joint associations between multiple metals mixture and DR risk among elderly diabetic population in China. A total of 1127 elderly adults (aged ≥ 60) with diabetes mellitus from a large-scale DR screening program in southern China included. Metals (beryllium, magnesium, chromium, manganese, iron, nickel, copper, arsenic, thallium and lead) in serum were quantified by inductively coupled plasma mass spectrometer. DR was diagnosed according to the consensus of the global DR project group. The relationships between metals and DR risks were estimated by logistic regression, Bayesian kernel machine regression (BKMR) and weighted quantile sum (WQS) regression. Of 1127 older adults with diabetes mellitus, there were 324 DR and 803 non-DR participants. Logistic regression models found serum magnesium and iron were negatively related to DR risks. Both BKMR model and WQS regression revealed that higher serum levels of multiple metals mixture were associated with lower risks of DR, with Be contributing the most to the overall effect. Additionally, in subgroup analyses, the interaction between beryllium and blood pressure on DR risk was also observed (<i>P</i><sub>interaction</sub> = 0.008). Overall, these results provided new evidence of direct association between multiple metals mixture and DR risk among elderly diabetic population in China.</p>

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Association between multiple metals mixture and diabetic retinopathy in older adults with diabetes mellitus: a cross-sectional study in China

  • Shuren Ding,
  • Yirong Xie,
  • Feng Wang,
  • Jieyi Liu,
  • Hongya Li,
  • Heng Su,
  • Zhiqiang Zhao,
  • Qing Wei,
  • Shurong Pi,
  • Fubin Chen,
  • Qian Gu,
  • Baixiang Xiao,
  • Yun He

摘要

Previous studies have linked single metal with diabetic retinopathy (DR), but information about the combined effects of multiple metals mixture was scarce. Thus, we performed this cross-sectional study to investigate the single and joint associations between multiple metals mixture and DR risk among elderly diabetic population in China. A total of 1127 elderly adults (aged ≥ 60) with diabetes mellitus from a large-scale DR screening program in southern China included. Metals (beryllium, magnesium, chromium, manganese, iron, nickel, copper, arsenic, thallium and lead) in serum were quantified by inductively coupled plasma mass spectrometer. DR was diagnosed according to the consensus of the global DR project group. The relationships between metals and DR risks were estimated by logistic regression, Bayesian kernel machine regression (BKMR) and weighted quantile sum (WQS) regression. Of 1127 older adults with diabetes mellitus, there were 324 DR and 803 non-DR participants. Logistic regression models found serum magnesium and iron were negatively related to DR risks. Both BKMR model and WQS regression revealed that higher serum levels of multiple metals mixture were associated with lower risks of DR, with Be contributing the most to the overall effect. Additionally, in subgroup analyses, the interaction between beryllium and blood pressure on DR risk was also observed (Pinteraction = 0.008). Overall, these results provided new evidence of direct association between multiple metals mixture and DR risk among elderly diabetic population in China.