Influences Of Urinary Metals Concentrations And Food Intake Patterns On Hyperuricemia Among The Urban Elderly Residents In China

Part One:Associations of urinary metals levels with hyperuricemiaObjective:The present study aimed to investigate the associations between urinary metals concentrations and hyperuricemia among a Chinese urban elderly population.Methods:Based on the baseline participants(n=9411,≥60 years,having long-term residence permits of Shenzhen city)from the Shenzhen Aging Related Disorder Cohort,after removing the individuals with self-reported nephropathy(n=36)and estimated glomerular filtration rate of less than or equal to 60m L/min per 1.73m~2(n=1022),and excluding the individuals(n=1845)with missing data on any one of the study variables,6508 individuals were finally included in this analysis.We measured urinary concentrations of metals among the participants by inductively coupled plasma mass spectrometry(ICP-MS),estimated influences of urinary metals concentrations on the risk of hyperuricemia using Logistic regression models,then further assessed the dose-response associations between urinary metals concentrations and the risk of hyperuricemia using restricted cubic spline(RCS)functions.Results:After adjusted for potential confounders(including age,sex,education levels,marital status,active smoking,passive smoking,drinking consumption,hypertension,diabetes,hyperlipidemia,estimated glomerular filtration rate,body mass index and urinary creatinine),individual metal unconditional Logistic regression models showed that urinary concentrations of vanadium,chromium,iron,nickel,zinc or arsenic were associated with hyperuricemia risk.After adjusted for the same potential confounders fitted in single-metal unconditional Logistic regression models,multiple-metal unconditional Logistic regression models(including urinary concentrationsof vanadium,iron,nickel,arsenic or zinc)indicated that urinary concentrations of vanadium,iron,nickel,zinc or arsenic were associated with hyperuricemia risk;with an IQR increase in urinary concentration of each metal,the corresponding OR for urinary vanadium,iron,nickel,zinc or arsenic was 0.88(95%CI:0.81,0.95),0.73(95%CI:0.67,0.80),0.91(95%CI:0.84,0.98),1.48(95%CI:1.33,1.66),1.33(95%CI:1.21,1.45),respectively.Multiple-metal unconditional Logistic regression models revealed non association between urinary chromium concentrations and the risk of hyperuricemia(P>0.05).Restricted cubic spline functions indicated only non-linear association of urinary vanadium concentrations with the risk of hyperuricemia(P for overall<0.05,P for nonlinear<0.05).Conclusions:Urinary vanadium,iron or nickel concentrations were negatively associated with the risk of hyperuricemia;the corresponding OR was 0.88(95%CI:0.81,0.95)or 0.73(95%CI:0.67,0.80),0.91(95%CI:0.84,0.98)with an IQR increase in urinary vanadium,iron or nickel concentrations.Moreover,urinary zinc or arsenic concentratons were positively associated with hyperuricemia risk,the corresponding OR was 1.48(95%CI:1.33,1.66)or 1.33(95%CI:1.21,1.45)with an IQR increase in urinary concentrations of zinc or arsenic.RCS function revealed a negative non-linear dose-response association between urinary vanadium concentration and the risk of hyperuricemia.Part Two:Effects of food intake patterns and its interactions with urinary metals concentrations on hyperuricemiaObjective:This study aimed to reveal effects of food intake patterns and its interactions with urinary metals concentrations on the risk of hyperuricemia among a Chinese urban elderly population.Methods:Participants involved in this part were the same as those in Part One.Unconditional Logistic regression models were used to analyze effects of frequencies of various dietary intake on the risk of hyperuricemia.Factor analysis were used to identify food intake patterns associated with hyperuricemia.Unconditional Logistic regression models were used to estimate effects of food intake patterns scores and its interactions with urinary metals concentrations on the risk of hyperuricemia among the elderly.Results:After adjusted for the same covariates in individual metal unconditional Logistic regression models mentioned in Part One,unconditional Logistic regression analyzes showed that a positive association between frequency of rice or sea fish intake and hyperuricemia risk as well as a negative association between frequency of wheat,egg,bean or milk intake and hyperuricemia risk.Factor analysis identified the associations between the seven kinds of food intake patterns(including freshwater shrimp-and shell-cephalopod,sea fish-,shell-and shrimp,wheat,egg-milk,vegetable,pickle-bacon,freshwater fish)and hyperuricemia risk.After adjusted for the same covariates in the individual metal unconditional Logistic regression models in Part One,unconditional Logistic regression analyzes revealed that relative to individuals in the corresponding lowest quartiles of urinary levels of each metal,the adjusted OR for individuals in the third or fourth quantiles for intaking wheat pattern was 0.85(95%CI:0.73,0.99)or 0.77(95%CI:0.66,0.90),the adjusted ORs for individuals in the third or fourth quantiles for intaking egg-milk pattern corresponded to 0.75(95%CI:0.64,0.88)or 0.79(95%CI:0.67,0.92).Furthermore,urinary vanadium,iron or nickel levels with score of intaking wheat or egg-milk exhibited a negative scale additive interaction on hyperuricemia risk,but urinary zinc or arsenic levels with score of intaking wheat or egg-milk had a positive additive interaction on hyperuricemia risk.Conclusions:Intaking wheat or egg-milk was a significant associated with high risk of hyperuricemia.We found the presence of a positive additive interaction between intaking wheat or egg-milk pattern and urinary vanadium,iron or nickel levels on hyperuricemia risk,in addition to a negative additive interaction between intaking wheat or egg-milk pattern and urinary zinc or arsenic levels on hyperuricemia risk.