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The subjects in our study were examined and recruited between April 2014 and July 2016. The source population consisted of community residents in Suzhou City. We selected both cases and controls from the same City for the reason of more similar living environment and dietary habits comparing to different cities, which may be confounders for type 2 diabetes.
The diagnostic criteria for new cases of diabetes were based on blood glucose levels, defined as random plasma glucose concentrations ≥ 11.1 mmol/L plus symptoms of diabetes, 2-hour post-load oral glucose tolerance test (OGTT) ≥ 11.1 mmol/L, or fasting plasma glucose (FPG) ≥ 7.0 mmol/L. In addition, an HbA1c ≥ 6.5% has been accepted as a diagnostic criterion for DM. Adults who were selected as newly diagnosed cases should not have been previously diagnosed with type 2 diabetes by a physician and should not be current or past users of any oral hypoglycemic drugs or insulin. However, the definitions of newly diagnosed diabetes were determined after professional medical discussions with learned and experienced endocrinologists from the physical examination center.
Each subject donated 5-mL venous blood samples for subsequent blood testing. FPG was assayed with an automated biochemical analyzer (Randox Laboratories Ltd., UK) using the enzymatic colorimetric method. Clinical laboratory technicians working in Nanjing Prevention and Treatment Center for Occupational Diseases carried out the experiment according to standard operation procedures.
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Subject information was collected via questionnaire administered by trained interviewers in the form of face-to-face interviews. The questionnaire generally included demographic data, past and present medical conditions, pharmaceutical preparations, physical activity and diet during daily life, hereditary factors, drinking status, and smoking and passive smoking status. In our study, ever drinkers were identified as subjects who drank a bottle of beer or 50 g of wine per day for at least one year, and everyone else was classified as a never drinker. Workers who had one cigarette per day for at least one year were identified as ever smokers, and all others were never smokers.
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In the first round of selection, subjects who had been diagnosed with diabetes by professional endocrinologists and had being undergoing treatment or taking medication previously or presently were excluded from our study, as we sought newly diagnosed patients who had never undergone therapeutic treatment.
For the following analyses, we excluded subjects with missing blood samples, missing blood glucose data, or abnormal blood biochemical levels, which would probably have resulted in abnormal plasma outputs of metal elements. Adults whose blood did not qualify for plasma detection were also excluded. In addition, we excluded participants with missing investigative or physical examination data (e.g., missing height, weight, systolic or diastolic pressure, smoking or drinking status, total cholesterol or triglycerides, etc.).
Each recruited newly diagnosed case of type 2 diabetes was well matched with 1-4 controls. The cases were selected without any restriction on age or sex, while the controls, which were frequency-matched to the cases by age, gender, and BMI, consisted of individuals from the same community who were seeking health care from the Suzhou Center for Disease Control and Prevention at the same time. The final participant population consisted of 551 subjects (122 newly diagnosed cases of type 2 diabetes and 429 matched controls) from a community physical examination center in Suzhou city of Jiangsu Province, China.
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This project was approved by the Ethics Committee of Nanjing Medical University. Written informed consent was obtained from each individual. Ethical guidelines were followed throughout the whole study period.
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We determined the concentrations of 20 metals in plasma in the following steps. In brief, the frozen plasma samples were stored in a refrigerator at 5 ℃ 3 h before sample preparation and completely thawed at room temperature immediately before the experiment, followed by homogenizing on a vortex mixer. A 200-μL plasma sample was pipetted into a 10-mL centrifuge tube (LabServ. Thermo Fisher Scientific, USA) containing 200 μL of 100-μg/L interior label, and then the volume was adjusted to 4.0 mL with diluent prepared with 65% (v/v) highly purified Triton X-100 (Sigma-Aldrich), 65% nitric acid HNO3 (Merck KGaA, Germany), and purified water (Wahaha Purified Water, China). When the final homogenization was complete, we measured metal concentrations in the composite samples with an inductively-coupled plasma mass spectrometer on the basis of an octupole-based collision/reaction cell (Thermo, iCAP-Q ICP-MS, USA). Furthermore, internal quality control samples with every batch were detected after standardization. The detection limits of all metal elements are demonstrated in Table 1.
Table 1. Detection Limits of ICP-MS for Metal Elements
Elements Detection Limits (μg/L) Vanadium 0.0040 Chromium 0.0153 Manganese 0.0213 Iron 0.4043 Cobalt 0.0015 Nickel 0.0540 Copper 0.0329 Zinc 0.3189 Arsenic 0.0181 Selenium 0.0000 Rubidium 0.0234 Strontium 0.0435 Ruthenium 0.0019 Rhodium 0.0002 Palladium 0.0073 Argentum 0.0054 Cadmium 0.0023 Cesium 0.0016 Barium 0.0642 Lanthanum 0.0011 -
Measurement data are expressed as mean ± SD (x±s), and data with a skewed distribution are described as median and interquartile ranges. Differences among groups were analyzed by nonparametric tests, student t-test, or one-way ANOVA. Qualitative data were described as percentages and analyzed using the chi-square (χ2) test or Fisher's exact test as indicated. Crude and adjusted odds ratios (ORs) were determined with 95% confidence intervals (95% CIs) by multivariate logistic regression.
Results were considered statistically significant at P < 0.05. We entered all data into a computerized database using the statistical analysis software Epidata 3.1. All analyses were performed using the SPSS software (Version 22.0, SPSS Inc., USA) and SAS 9.1.3 (SAS Institute, Cary, NC).
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Table 2 shows the basic characteristics of all subjects. A total of 551 participants were analyzed in this study. There were more female subjects than male ones in each group and in the total population. Approximately 216 (39.2%) out of 551 subjects were male, whereas the remaining 335 (60.8%) were female. The age range of all subjects was 40-92, and the mean age was 66.48, 66.25, and 66.43 years for controls, newly diagnosed type 2 diabetes patients, and the total population, respectively. Most of our population disapproved of smoking and drinking: 84.0% of study subjects were never smokers, and 16.0% were ever smokers. The ratio of never to ever drinkers was 89.7% and 10.3%, respectively. There were no significant differences between cases and controls with respect to age, gender, BMI, and smoking status; however, cases were more likely than controls to be ever drinkers. The percentage of current drinkers in cases was significantly higher than in controls (15.6% vs. 8.9%, P < 0.05). With respect to family history, the case group was more likely to have a family history of diabetes than the controls, with a prevalence of 14.8% in cases and 4.7% in controls. However, the mean level of FPG in newly diagnosed diabetes was significantly higher than that in controls (7.55 vs. 5.67 mmol/L, P < 0.05).
Table 2. Descriptive Characteristics of New Diagnosed Cases of Type 2 Diabetes and Controls
Variables All (N = 551) Cases (N = 122) Controls (N = 429) P Gender, n (%) Male 216 (39.2) 43 (35.2) 173 (40.3) 0.310a Female 335 (60.8) 79 (64.8) 256 (59.7) Age, years 66.43 ± 9.36 66.25 ± 9.46 66.48 ± 9.34 0.809b < 66, n (%) 234 (42.5) 55 (45.1) 179 (41.7) 0.880a 66-70, n (%) 136 (24.7) 25 (20.5) 111 (25.9) > 70, n (%) 181 (32.8) 42 (34.4) 139 (32.4) BMI, kg/m2 24.67 ± 3.32 25.08 ± 3.74 24.55 ± 3.18 0.151b Smoking status, n (%) Never 463 (84.0) 100 (82.0) 363 (84.6) 0.481a Ever 88 (16.0) 22 (18.0) 66 (15.4) Drinking status, n (%) Never 494 (89.7) 103 (84.4) 391 (91.1) 0.032a Ever 57 (10.3) 19 (15.6) 38 (8.9) Family history, n (%) No 513 (93.1) 104 (85.2) 409 (95.3) 0.000a Yes 38 (6.9) 18 (14.8) 20 (4.7) FPG, mmol/L 6.09 ± 3.18 7.55 ± 2.14 5.67 ± 3.30 0.000b Note. aχ2 test for the distribution between cases and controls. bStudent t-test for mean comparison between cases and controls. -
Table 3 shows the blood levels of 20 metal elements in our study participants. There were significant differences between cases and controls in plasma vanadium concentration: the median concentration of vanadium was 0.234 μg/L in the case group and 0.177 μg/L in the control group (P < 0.05). Similarly, blood levels of chromium, manganese, copper, zinc, and cadmium were higher in cases than those in controls (P < 0.05): the corresponding concentrations were 2.286 μg/L in cases vs. 1.898 μg/L in controls for chromium, 2.725 μg/L vs. 1.828 μg/L for manganese, 932.164 μg/L vs. 786.388 μg/L for copper, 634.382 μg/L vs. 575.205 μg/L for zinc, and 0.096 μg/L vs. 0.065 μg/L for cadmium. Participants with diabetes had significantly higher concentrations of arsenic, selenium, strontium, palladium, cesium, and barium than those in the non-diabetic group (P < 0.05): their comparative plasma levels were 0.754 μg/L in diabetes vs. 0.536 μg/L in non-diabetes for arsenic, 18.565 μg/L vs. 15.447 μg/L for selenium, 33.248 μg/L vs. 30.539 μg/L for strontium, 0.373 μg/L vs. 0.231 μg/L for palladium, 0.957 μg/L vs. 0.779 μg/L for cesium, and 8.173 μg/L vs. 4.802 μg/L for barium. However, there was no significant difference in the blood concentrations of iron, cobalt, nickel, rubidium, ruthenium, rhodium, argentum, and lanthanum between cases and controls with respect to the median values.
Table 3. Metal Concentrations in New Diagnosed Diabetes and Controls
Variables All Cases Controls Pa Median
(μg/L)Quartile Range
(μg/L)Median
(μg/L)Quartile Range
(μg/L)Median
(μg/L)Quartile Range
(μg/L)Vanadium 0.191 0.138 0.234 0.180 0.177 0.125 0.000 Chromium 1.952 1.114 2.286 1.389 1.898 1.048 0.000 Manganese 1.954 1.242 2.725 1.930 1.828 0.944 0.000 Iron 1117.162 451.861 1174.648 459.733 1104.439 442.876 0.139 Cobalt 0.294 0.124 0.292 0.132 0.297 0.122 0.563 Nickel 6.478 3.640 5.968 3.903 6.551 3.570 0.191 Copper 815.755 261.226 932.164 268.340 786.388 244.672 0.000 Zinc 590.108 196.973 634.382 191.369 575.205 201.633 0.000 Arsenic 0.615 0.784 0.754 0.584 0.536 0.790 0.002 Selenium 16.390 11.875 18.565 9.279 15.447 12.538 0.000 Rubidium 277.661 82.564 274.967 66.249 278.579 93.801 0.501 Strontium 31.456 12.724 33.248 14.153 30.539 11.489 0.000 Ruthenium 0.043 0.061 0.046 0.069 0.042 0.057 0.398 Rhodium 0.000 0.003 0.000 0.003 0.000 0.003 0.545 Palladium 0.287 0.716 0.373 0.609 0.231 0.693 0.002 Argentum 0.411 0.462 0.503 0.398 0.390 0.497 0.730 Cadmium 0.071 0.065 0.096 0.102 0.065 0.061 0.000 Cesium 0.821 0.404 0.957 0.375 0.779 0.382 0.000 Barium 5.115 4.633 8.173 13.656 4.802 3.202 0.000 Lanthanum 0.035 0.034 0.038 0.032 0.035 0.036 0.333 Note. aNonparametric test for the comparison of metal levels in abnormal distribution. -
We divided the subjects' plasma metal concentrations into tertiles to analyze the association between diabetes prevalence and metal content. Serum iron, cobalt, nickel, rubidium, ruthenium, rhodium, argentum, and lanthanum were not associated with diabetes risk (Table 4). However, for the other metals, we observed statistically significant correlations with increased diabetes risk. After adjusting for confounders, the adjusted OR values and 95% CI of diabetes of the third tertiles (the highest group) comparing minimum tertiles (the lowest group) for vanadium, chromium, manganese, copper, zinc, arsenic, selenium, strontium, palladium, cadmium, cesium, and barium were 3.589 (2.040-6.314), 2.219 (1.319-3.733), 7.880 (4.169-14.893), 6.862 (3.644-12.920), 2.261 (1.285-3.979), 2.204 (1.244-3.905), 6.138 (3.012-12.509), 2.151 (1.273-3.636), 2.236 (1.266-3.952), 2.511 (1.486-4.245), 3.908 (2.223-6.869), and 6.184 (3.448-11.093), respectively, and the second tertiles (the middle group) comparing minimum tertiles for vanadium, manganese, copper, zinc, arsenic, selenium, palladium, and cesium were 2.100 (1.178-3.744), 2.528 (1.286-4.969), 2.796 (1.456-5.368), 1.964 (1.132-3.407), 3.436 (1.956-6.037), 8.134 (4.088-16.182), 2.409 (1.370-4.237), and 1.847 (1.015-3.361), respectively. Furthermore, the adjusted OR increased with increasing concentration of vanadium, manganese, copper, zinc, and cesium per tertile (P < 0.05).
Table 4. Comparisons of Diabetes risk According to the Three Tertiles of Plasma Metals
Variables Q1 (lowest)
(μg/L)Q2 (middle)
(μg/L)Q3 (highest)
(μg/L)Pb Vanadium < 0.151 0.151- 0.235 Case: N (%) 22 (18.03) 40 (32.79) 60 (49.18) 0.000 Control: N (%) 162 (37.76) 143 (33.33) 124 (28.91) All (%) 184 (33.39) 183 (33.22) 184 (33.39) Adjusted OR (95% CIs)a 1.000 2.100 (1.178-3.744) 3.589 (2.040-6.314) Chromium < 1.623 1.623-2.321 > 2.321 Case: N (%) 30 (24.59) 33 (27.05) 59 (48.36) 0.000 Control: N (%) 152 (35.43) 151 (35.20) 126 (29.37) All (%) 182 (33.03) 184 (33.39) 185 (33.58) Adjusted OR (95% CIs)a 1.000 1.066 (0.605-1.878) 2.219 (1.319-3.733) Manganese < 1.671 1.671-2.416 > 2.416 Case: N (%) 14 (11.48) 33 (27.05) 75 (61.47) 0.000 Control: N (%) 169 (39.39) 152 (35.43) 108 (25.18) All (%) 183 (33.21) 185 (33.58) 183 (33.21) Adjusted OR (95% CIs)a 1.000 2.528 (1.286-4.969) 7.880 (4.169-14.893) Iron < 988.245 988.245-1293.406 > 1293.406 Case: N (%) 34 (27.87) 45 (36.89) 43 (35.24) 0.246 Control: N (%) 150 (34.97) 139 (32.40) 140 (32.63) All (%) 184 (33.39) 184 (33.39) 183 (33.22) Adjusted OR (95% CIs)a 1.000 1.418 (0.847-2.373) 1.591(0.900-2.814) Cobalt < 0.259 0.259-0.340 > 0.340 Case: N (%) 45 (36.89) 38 (31.15) 39 (31.96) 0.520 Control: N (%) 140 (32.63) 147 (34.27) 142 (33.10) All (%) 185 (33.58) 185 (33.58) 181 (32.84) Adjusted OR (95% CIs)a 1.000 0.820 (0.495-1.357) 0.822 (0.496-1.364) Nickel < 5.365 5.365-7.713 > 7.713 Case: N (%) 53 (43.44) 30 (24.59) 39 (31.97) 0.074 Control: N (%) 130 (30.30) 154 (35.90) 145 (33.80) All (%) 183 (33.22) 184 (33.39) 184 (33.39) Adjusted OR (95% CIs)a 1.000 0.416 (0.245-0.706) 0.637 (0.383-1.060) Copper < 729.661 729.661-901.400 > 901.400 Case: N (%) 15 (12.30) 37 (30.32) 70 (57.38) 0.000 Control: N (%) 168 (39.16) 147 (34.27) 114 (26.57) All (%) 183 (33.22) 184 (33.39) 184 (33.39) Adjusted OR (95% CIs)a 1.000 2.796 (1.456-5.368) 6.862 (3.644-12.920) Zinc < 529.777 529.777-649.232 > 649.232 Case: N (%) 27 (22.13) 43 (35.25) 52 (42.62) 0.002 Control: N (%) 156 (36.36) 141 (32.87) 132 (30.77) All (%) 183 (33.22) 184 (33.39) 184 (33.39) Adjusted OR (95% CIs)a 1.000 1.964 (1.132-3.407) 2.261 (1.285-3.979) Arsenic < 0.389 0.389-0.915 > 0.915 Case: N (%) 22 (18.03) 57 (46.72) 43 (35.25) 0.008 Control: N (%) 162 (37.76) 127 (29.60) 140 (32.64) All (%) 184 (33.39) 184 (33.39) 183 (33.22) Adjusted OR (95% CIs)a 1.000 3.436 (1.956-6.037) 2.204 (1.244-3.905) Selenium < 12.774 12.774-19.825 > 19.825 Case: N (%) 13 (10.66) 60 (49.18) 49 (40.16) 0.000 Control: N (%) 171 (39.86) 124 (28.90) 134 (31.24) All (%) 184 (33.39) 184 (33.39) 183 (33.22) Adjusted OR (95% CIs)a 1.000 8.134 (4.088-16.182) 6.138 (3.012-12.509) Rubidium < 251.164 251.164-300.669 > 300.669 Case: N (%) 32 (26.23) 54 (44.26) 36 (29.51) 0.615 Control: N (%) 152 (35.43) 129 (30.07) 148 (34.50) All (%) 184 (33.39) 183 (33.22) 184 (33.39) Adjusted OR (95% CIs)a 1.000 2.286 (1.354-3.860) 1.057 (0.578-1.933) Strontium < 28.225 28.225-36.059 > 36.059 Case: N (%) 28 (22.95) 40 (32.79) 54 (44.26) 0.001 Control: N (%) 156 (36.36) 144 (33.57) 129 (30.07) All (%) 184 (33.39) 184 (33.39) 183 (33.22) Adjusted OR (95% CIs)a 1.000 1.505 (0.866-2.616) 2.151 (1.273-3.636) Ruthenium < 0.027 0.027-0.065 > 0.065 Case: N (%) 34 (27.87) 45 (36.89) 43 (35.24) 0.246 Control: N (%) 150 (34.97) 139 (32.40) 140 (32.63) All (%) 184 (33.39) 184 (33.39) 183 (33.22) Adjusted OR (95% CIs)a 1.000 1.349 (0.803-2.267) 1.277 (0.749-2.179) Rhodium < 0.000 0.000-0.003 > 0.003 Case: N (%) 64 (52.46) 37 (30.33) 21 (17.21) 0.286 Control: N (%) 227 (52.91) 87 (20.28) 115 (26.81) All (%) 291 (52.81) 124 (22.50) 136 (24.69) Adjusted OR (95% CIs)a 1.000 1.568 (0.962-2.557) 0.686 (0.394-1.194) Palladium < 0.100 0.100-0.493 > 0.493 Case: N (%) 23 (18.85) 53 (43.44) 46 (37.71) 0.004 Control: N (%) 160 (37.30) 131 (30.54) 138 (32.16) All (%) 183 (33.22) 184 (33.39) 184 (33.39) Adjusted OR (95% CIs)a 1.000 2.409 (1.370-4.237) 2.236 (1.266-3.952) Argentum < 0.300 0.300-0.636 > 0.636 Case: N (%) 36 (29.51) 48 (39.34) 38 (31.15) 0.801 Control: N (%) 147 (34.27) 137 (31.93) 145 (33.80) All (%) 183 (33.21) 185 (33.58) 183 (33.21) Adjusted OR (95% CIs)a 1.000 1.458 (0.870-2.442) 0.929 (0.544-1.587) Cadmium < 0.051 0.051-0.096 > 0.096 Case: N (%) 28 (22.95) 33 (27.05) 61 (50.00) 0.000 Control: N (%) 153 (35.66) 152 (35.43) 124 (28.91) All (%) 181 (32.84) 185 (33.58) 185 (33.58) Adjusted OR (95% CIs)a 1.000 1.086 (0.617-1.912) 2.511 (1.486-4.245) Cesium < 0.700 0.700-0.951 > 0.951 Case: N (%) 21 (17.21) 37 (30.33) 64 (52.46) 0.000 Control: N (%) 163 (38.00) 147 (34.27) 119 (27.73) All (%) 184 (33.39) 184 (33.39) 183 (33.22) Adjusted OR (95% CIs)a 1.000 1.847 (1.015-3.361) 3.908 (2.223-6.869) Barium < 4.134 4.134-6.786 > 6.786 Case: N (%) 18 (14.75) 28 (22.95) 76 (62.30) 0.000 Control: N (%) 165 (38.46) 157 (36.60) 107 (24.94) All (%) 183 (33.21) 185 (33.58) 183 (33.21) Adjusted OR (95% CIs)a 1.000 1.583 (0.823-3.046) 6.184 (3.448-11.093) Lanthanum < 0.026 0.026-0.049 > 0.049 Case: N (%) 36 (29.50) 43 (35.25) 43 (35.25) 0.379 Control: N (%) 148 (34.50) 140 (32.63) 141 (32.87) All (%) 184 (33.39) 183 (33.22) 184 (33.39) Adjusted OR (95% CIs)a 1.000 1.236 (0.741-2.062) 1.202 (0.712-2.029) Note. aAdjusted for age, gender, BMI, family history, smoking and drinking status in the logistic regression model. bχ2 test for the distribution of different metal levels.
doi: 10.3967/bes2017.064
Association between Plasma Metal Levels and Diabetes Risk:a Case-control Study in China
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Abstract:
Objective Many metals, some of which have been classified as environmental endocrine disruptors, are used extensively in everyday consumer products and are ubiquitous in our living environment.In the present study, we aimed to explore the associations between the prevalence risk of type 2 diabetes and plasma levels of 20 trace elements as well as those of heavy metals in a Han Chinese population. Methods We conducted a case-control study to investigate the associations between plasma concentrations of 20 metals and diabetes in Jiangsu province.A total of 122 newly diagnosed cases of type 2 diabetes and 429 matched controls were recruited from community physical examinations in Suzhou City of Jiangsu Province.Plasma metal levels were measured by inductively-coupled plasma mass spectrometry. Results After adjusting for confounders, plasma vanadium, chromium, manganese, copper, zinc, arsenic, selenium, strontium, palladium, cadmium, cesium, and barium were associated with diabetes risk (P < 0.05).The adjusted OR increased with increasing concentration of vanadium, manganese, copper, zinc, and cesium. Conclusion Many metals, including manganese, copper, zinc, arsenic, selenium, and cadmium in plasma, are associated with the morbidity of diabetes.Monitoring of environmental metal levels and further studies are urgently needed. -
Table 1. Detection Limits of ICP-MS for Metal Elements
Elements Detection Limits (μg/L) Vanadium 0.0040 Chromium 0.0153 Manganese 0.0213 Iron 0.4043 Cobalt 0.0015 Nickel 0.0540 Copper 0.0329 Zinc 0.3189 Arsenic 0.0181 Selenium 0.0000 Rubidium 0.0234 Strontium 0.0435 Ruthenium 0.0019 Rhodium 0.0002 Palladium 0.0073 Argentum 0.0054 Cadmium 0.0023 Cesium 0.0016 Barium 0.0642 Lanthanum 0.0011 Table 2. Descriptive Characteristics of New Diagnosed Cases of Type 2 Diabetes and Controls
Variables All (N = 551) Cases (N = 122) Controls (N = 429) P Gender, n (%) Male 216 (39.2) 43 (35.2) 173 (40.3) 0.310a Female 335 (60.8) 79 (64.8) 256 (59.7) Age, years 66.43 ± 9.36 66.25 ± 9.46 66.48 ± 9.34 0.809b < 66, n (%) 234 (42.5) 55 (45.1) 179 (41.7) 0.880a 66-70, n (%) 136 (24.7) 25 (20.5) 111 (25.9) > 70, n (%) 181 (32.8) 42 (34.4) 139 (32.4) BMI, kg/m2 24.67 ± 3.32 25.08 ± 3.74 24.55 ± 3.18 0.151b Smoking status, n (%) Never 463 (84.0) 100 (82.0) 363 (84.6) 0.481a Ever 88 (16.0) 22 (18.0) 66 (15.4) Drinking status, n (%) Never 494 (89.7) 103 (84.4) 391 (91.1) 0.032a Ever 57 (10.3) 19 (15.6) 38 (8.9) Family history, n (%) No 513 (93.1) 104 (85.2) 409 (95.3) 0.000a Yes 38 (6.9) 18 (14.8) 20 (4.7) FPG, mmol/L 6.09 ± 3.18 7.55 ± 2.14 5.67 ± 3.30 0.000b Note. aχ2 test for the distribution between cases and controls. bStudent t-test for mean comparison between cases and controls. Table 3. Metal Concentrations in New Diagnosed Diabetes and Controls
Variables All Cases Controls Pa Median
(μg/L)Quartile Range
(μg/L)Median
(μg/L)Quartile Range
(μg/L)Median
(μg/L)Quartile Range
(μg/L)Vanadium 0.191 0.138 0.234 0.180 0.177 0.125 0.000 Chromium 1.952 1.114 2.286 1.389 1.898 1.048 0.000 Manganese 1.954 1.242 2.725 1.930 1.828 0.944 0.000 Iron 1117.162 451.861 1174.648 459.733 1104.439 442.876 0.139 Cobalt 0.294 0.124 0.292 0.132 0.297 0.122 0.563 Nickel 6.478 3.640 5.968 3.903 6.551 3.570 0.191 Copper 815.755 261.226 932.164 268.340 786.388 244.672 0.000 Zinc 590.108 196.973 634.382 191.369 575.205 201.633 0.000 Arsenic 0.615 0.784 0.754 0.584 0.536 0.790 0.002 Selenium 16.390 11.875 18.565 9.279 15.447 12.538 0.000 Rubidium 277.661 82.564 274.967 66.249 278.579 93.801 0.501 Strontium 31.456 12.724 33.248 14.153 30.539 11.489 0.000 Ruthenium 0.043 0.061 0.046 0.069 0.042 0.057 0.398 Rhodium 0.000 0.003 0.000 0.003 0.000 0.003 0.545 Palladium 0.287 0.716 0.373 0.609 0.231 0.693 0.002 Argentum 0.411 0.462 0.503 0.398 0.390 0.497 0.730 Cadmium 0.071 0.065 0.096 0.102 0.065 0.061 0.000 Cesium 0.821 0.404 0.957 0.375 0.779 0.382 0.000 Barium 5.115 4.633 8.173 13.656 4.802 3.202 0.000 Lanthanum 0.035 0.034 0.038 0.032 0.035 0.036 0.333 Note. aNonparametric test for the comparison of metal levels in abnormal distribution. Table 4. Comparisons of Diabetes risk According to the Three Tertiles of Plasma Metals
Variables Q1 (lowest)
(μg/L)Q2 (middle)
(μg/L)Q3 (highest)
(μg/L)Pb Vanadium < 0.151 0.151- 0.235 Case: N (%) 22 (18.03) 40 (32.79) 60 (49.18) 0.000 Control: N (%) 162 (37.76) 143 (33.33) 124 (28.91) All (%) 184 (33.39) 183 (33.22) 184 (33.39) Adjusted OR (95% CIs)a 1.000 2.100 (1.178-3.744) 3.589 (2.040-6.314) Chromium < 1.623 1.623-2.321 > 2.321 Case: N (%) 30 (24.59) 33 (27.05) 59 (48.36) 0.000 Control: N (%) 152 (35.43) 151 (35.20) 126 (29.37) All (%) 182 (33.03) 184 (33.39) 185 (33.58) Adjusted OR (95% CIs)a 1.000 1.066 (0.605-1.878) 2.219 (1.319-3.733) Manganese < 1.671 1.671-2.416 > 2.416 Case: N (%) 14 (11.48) 33 (27.05) 75 (61.47) 0.000 Control: N (%) 169 (39.39) 152 (35.43) 108 (25.18) All (%) 183 (33.21) 185 (33.58) 183 (33.21) Adjusted OR (95% CIs)a 1.000 2.528 (1.286-4.969) 7.880 (4.169-14.893) Iron < 988.245 988.245-1293.406 > 1293.406 Case: N (%) 34 (27.87) 45 (36.89) 43 (35.24) 0.246 Control: N (%) 150 (34.97) 139 (32.40) 140 (32.63) All (%) 184 (33.39) 184 (33.39) 183 (33.22) Adjusted OR (95% CIs)a 1.000 1.418 (0.847-2.373) 1.591(0.900-2.814) Cobalt < 0.259 0.259-0.340 > 0.340 Case: N (%) 45 (36.89) 38 (31.15) 39 (31.96) 0.520 Control: N (%) 140 (32.63) 147 (34.27) 142 (33.10) All (%) 185 (33.58) 185 (33.58) 181 (32.84) Adjusted OR (95% CIs)a 1.000 0.820 (0.495-1.357) 0.822 (0.496-1.364) Nickel < 5.365 5.365-7.713 > 7.713 Case: N (%) 53 (43.44) 30 (24.59) 39 (31.97) 0.074 Control: N (%) 130 (30.30) 154 (35.90) 145 (33.80) All (%) 183 (33.22) 184 (33.39) 184 (33.39) Adjusted OR (95% CIs)a 1.000 0.416 (0.245-0.706) 0.637 (0.383-1.060) Copper < 729.661 729.661-901.400 > 901.400 Case: N (%) 15 (12.30) 37 (30.32) 70 (57.38) 0.000 Control: N (%) 168 (39.16) 147 (34.27) 114 (26.57) All (%) 183 (33.22) 184 (33.39) 184 (33.39) Adjusted OR (95% CIs)a 1.000 2.796 (1.456-5.368) 6.862 (3.644-12.920) Zinc < 529.777 529.777-649.232 > 649.232 Case: N (%) 27 (22.13) 43 (35.25) 52 (42.62) 0.002 Control: N (%) 156 (36.36) 141 (32.87) 132 (30.77) All (%) 183 (33.22) 184 (33.39) 184 (33.39) Adjusted OR (95% CIs)a 1.000 1.964 (1.132-3.407) 2.261 (1.285-3.979) Arsenic < 0.389 0.389-0.915 > 0.915 Case: N (%) 22 (18.03) 57 (46.72) 43 (35.25) 0.008 Control: N (%) 162 (37.76) 127 (29.60) 140 (32.64) All (%) 184 (33.39) 184 (33.39) 183 (33.22) Adjusted OR (95% CIs)a 1.000 3.436 (1.956-6.037) 2.204 (1.244-3.905) Selenium < 12.774 12.774-19.825 > 19.825 Case: N (%) 13 (10.66) 60 (49.18) 49 (40.16) 0.000 Control: N (%) 171 (39.86) 124 (28.90) 134 (31.24) All (%) 184 (33.39) 184 (33.39) 183 (33.22) Adjusted OR (95% CIs)a 1.000 8.134 (4.088-16.182) 6.138 (3.012-12.509) Rubidium < 251.164 251.164-300.669 > 300.669 Case: N (%) 32 (26.23) 54 (44.26) 36 (29.51) 0.615 Control: N (%) 152 (35.43) 129 (30.07) 148 (34.50) All (%) 184 (33.39) 183 (33.22) 184 (33.39) Adjusted OR (95% CIs)a 1.000 2.286 (1.354-3.860) 1.057 (0.578-1.933) Strontium < 28.225 28.225-36.059 > 36.059 Case: N (%) 28 (22.95) 40 (32.79) 54 (44.26) 0.001 Control: N (%) 156 (36.36) 144 (33.57) 129 (30.07) All (%) 184 (33.39) 184 (33.39) 183 (33.22) Adjusted OR (95% CIs)a 1.000 1.505 (0.866-2.616) 2.151 (1.273-3.636) Ruthenium < 0.027 0.027-0.065 > 0.065 Case: N (%) 34 (27.87) 45 (36.89) 43 (35.24) 0.246 Control: N (%) 150 (34.97) 139 (32.40) 140 (32.63) All (%) 184 (33.39) 184 (33.39) 183 (33.22) Adjusted OR (95% CIs)a 1.000 1.349 (0.803-2.267) 1.277 (0.749-2.179) Rhodium < 0.000 0.000-0.003 > 0.003 Case: N (%) 64 (52.46) 37 (30.33) 21 (17.21) 0.286 Control: N (%) 227 (52.91) 87 (20.28) 115 (26.81) All (%) 291 (52.81) 124 (22.50) 136 (24.69) Adjusted OR (95% CIs)a 1.000 1.568 (0.962-2.557) 0.686 (0.394-1.194) Palladium < 0.100 0.100-0.493 > 0.493 Case: N (%) 23 (18.85) 53 (43.44) 46 (37.71) 0.004 Control: N (%) 160 (37.30) 131 (30.54) 138 (32.16) All (%) 183 (33.22) 184 (33.39) 184 (33.39) Adjusted OR (95% CIs)a 1.000 2.409 (1.370-4.237) 2.236 (1.266-3.952) Argentum < 0.300 0.300-0.636 > 0.636 Case: N (%) 36 (29.51) 48 (39.34) 38 (31.15) 0.801 Control: N (%) 147 (34.27) 137 (31.93) 145 (33.80) All (%) 183 (33.21) 185 (33.58) 183 (33.21) Adjusted OR (95% CIs)a 1.000 1.458 (0.870-2.442) 0.929 (0.544-1.587) Cadmium < 0.051 0.051-0.096 > 0.096 Case: N (%) 28 (22.95) 33 (27.05) 61 (50.00) 0.000 Control: N (%) 153 (35.66) 152 (35.43) 124 (28.91) All (%) 181 (32.84) 185 (33.58) 185 (33.58) Adjusted OR (95% CIs)a 1.000 1.086 (0.617-1.912) 2.511 (1.486-4.245) Cesium < 0.700 0.700-0.951 > 0.951 Case: N (%) 21 (17.21) 37 (30.33) 64 (52.46) 0.000 Control: N (%) 163 (38.00) 147 (34.27) 119 (27.73) All (%) 184 (33.39) 184 (33.39) 183 (33.22) Adjusted OR (95% CIs)a 1.000 1.847 (1.015-3.361) 3.908 (2.223-6.869) Barium < 4.134 4.134-6.786 > 6.786 Case: N (%) 18 (14.75) 28 (22.95) 76 (62.30) 0.000 Control: N (%) 165 (38.46) 157 (36.60) 107 (24.94) All (%) 183 (33.21) 185 (33.58) 183 (33.21) Adjusted OR (95% CIs)a 1.000 1.583 (0.823-3.046) 6.184 (3.448-11.093) Lanthanum < 0.026 0.026-0.049 > 0.049 Case: N (%) 36 (29.50) 43 (35.25) 43 (35.25) 0.379 Control: N (%) 148 (34.50) 140 (32.63) 141 (32.87) All (%) 184 (33.39) 183 (33.22) 184 (33.39) Adjusted OR (95% CIs)a 1.000 1.236 (0.741-2.062) 1.202 (0.712-2.029) Note. aAdjusted for age, gender, BMI, family history, smoking and drinking status in the logistic regression model. bχ2 test for the distribution of different metal levels. -
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