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Exposure To Cadmium,Lead,Mercury,and Arsenic And Uric Acid Levels

Posted on:2024-09-18Degree:MasterType:Thesis
Country:ChinaCandidate:W H GaoFull Text:PDF
GTID:2544307064997799Subject:Public Health
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Objective:UA,as an antioxidant,may be involved in the oxidative stress caused by toxic metal exposures.The aim was to identify major toxic metals/metalloids that affected UA levels with a mixture exposure concept in the association model.Methods:From 2007–2016 National Health and Nutrition Examination Survey(NHANES),4794adults aged 20 years or older were involved.The data of general demographic characteristics,behavioral factors,disease history,physical examination indicators and laboratory test indicators were collected.Serum UA(SUA)and SUA to serum creatinine ratio(SUA/SCr)were used to estimate the UA levels in the study.Descriptive statistics were made for all demographic and other characteristics of the subjects.The measurement data that do not conform to the normal distribution are represented by the median and interquartile distance(IQR),and the classification data is represented by the number of use cases(component ratio).We assessed the associations between toxic metals and UA levels using linear regression and Bayesian kernel machine regression(BKMR).Subgroup analyses were performed based on baseline characteristics such as(male and female),and age(<40 years and≥40 years).Results:1.Among the included subjects,2452(51.1%)were males and 2342(48.9%)were females;The median age was 44 years,the baseline median SUA level was 5.30(4.40,6.30)mg/d L,and those with gout and hyperuricemia were 1.9%and 14.7%,respectively.2.The detection rate of several metals/metals in the study population is≥80%.There was a weak to high correlation among all metals(correlation coefficient r ranged from-0.02 to 0.63),and there was a strong correlation between blood Pb and urine Pb(r=0.63).3.Gender-based subgroup analysis showed that toxic mixtures were positively correlated with SUA/SCr and SUA levels in both men and women,among which blood Cd and Pb and urine Cd,Pb and As were the main contributors to the combined effects.Blood Pb of male and female(βmale=0.978,95%CI:0.760~1.213);βfemale=0.651,95%CI:0.255~1.047)and urine Cd(βmale=0.461,95%CI:0.262~0.660;βfemale=0.252,95%CI:0.030~0.474)were positively correlated with SUA/SCr,while urinary Pb(βmale=-0.720,95%CI:-0.915~-0.525;βfemale=-0.462,95%CI:-0.757~-0.167)was negatively correlated with SUA/SCr level.Blood Cd(βmale=-0.237,95%CI:-0.439~-0.035)was negatively associated with SUA/SCr levels only in males.No correlation was found between blood/urine Hg and SUA/SCr.We also found a potential gender difference in urinary As,with urinary As exposure(βmale=0.206,95%CI:0.060~0.351)only having a significant positive association with SUA/SCr levels in males.The above conclusions were also found in the results of our analysis of SUA.Age-based subgroup analysis showed that toxic mixtures were positively correlated with SUA/SCr and SUA levels only in the age group≥40 years and older.Blood Pb(β<40 years=0.514,95%CI:0.176~0.853;β≥40 years=1.195,95%CI:0.900~1.490)and urinary Cd(β<40 years=0.292,95%CI:0.134~0.450;β≥40 years=0.539,95%CI:0.291~0.786)levels were positively correlated with SUA/SCr levels in different age groups,while urinary Pb(β<40 years=-0.297,95%CI:-0.552~-0.006;β≥40 years=-0.666,95%CI:-0.897~-0.434)showed a negative correlation with SUA/SCr levels in the two age groups.We further found similar conclusions in the results of our analysis of SUA.Conclusions:The prevalence of hyperuricemia is high in American adults,and exposure to multiple toxic metal mixtures is positively correlated with UA.Blood Pb may be the most stable and dominant factor driving this association.Blood Pb,urinary Cd and urinary As were positively correlated with SUA/SCr,while urinary Pb was negatively correlated.The association was stronger in the40 and older age group.This study highlights the importance of using SUA/SCr levels(and not just SUA levels)to assess the independent and combined effects of Pb,Cd,Hg,and As and their mixtures.
Keywords/Search Tags:Bayesian kernel machine regression (BKMR), Mixtures, Toxic metals/metalloids, Joint effects, Uric acid
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