Background:　Mounting　evidence　suggests　a　correlation　between　heavy　metals　exposure　and　diabetes.　Diabetic　retinopathy　(DR)　is　a　prevalent　and　irreversible　complication　of　diabetes　that　can　result　in　blindness.　However,　studies　focusing　on　the　effects　of　exposure　to　heavy　metals　on　DR　remain　scarce.　Thus,　this　study　aimed　to　investigate　the　potential　correlation　between　heavy　metals　exposure　and　DR.　Methods:　A　total　of　1,146　diabetics　from　the　National　Health　and　Nutrition　Examination　Survey　(NHANES)　between　2005　and　2018　were　included　in　this　study.　Heavy　metal　levels　were　measured　via　urine　testing.　Weighted　logistic　regression,　Bayesian　kernel　machine　regression　(BKMR),　weighted　quantile　sum　(WQS)　regression,　and　restricted　cubic　spline　(RCS)　were　utilized　to　investigate　the　potential　relationships　between　exposure　to　10　heavy　metals　and　DR.　Finally,　subgroup　analysis　was　conducted　based　on　the　glycemic　control　status.　Results:　Among　the　1,146　participants,　239　(20.86%)　were　diagnosed　with　DR.　Those　with　DR　had　worse　glycemic　control　and　a　higher　prevalence　of　chronic　kidney　disease　compared　to　those　without　DR.　Moreover,　both　the　WQS　regression　and　BKMR　models　demonstrated　a　positive　relationship　between　exposure　to　mixed　heavy　metals　and　the　risk　of　DR.　The　results　of　weighted　logistic　regression　revealed　a　positive　correlation　between　cobalt　(Co)　and　antimony　(Sb)　exposure　and　the　risk　of　DR　(OR　=　1.489,　95%CI:　1.064–2.082,　p　=　0.021;　OR　=　1.475,　95%　CI:　1.084–2.008,　p　=　0.014),　while　mercury　(Hg)　exposure　was　found　to　promote　DR　exclusively　in　the　group　with　good　glycemic　control　(OR　=　1.509,　95%　CI:　1.157–1.967,　p　=　0.003).　These　findings　were　corroborated　by　the　results　of　the　RCS　analysis.　Conclusion:　Heavy　metal　exposure　is　associated　with　an　increased　risk　of　DR,　especially　Sb,　Co,　and　Hg　exposure.　Nevertheless,　well-designed　prospective　studies　are　warranted　to　validate　these　findings.　Copyright　©　2024　Meng,　Gu,　Cai,　He,　Lai　and　Qiu.