| Literature DB >> 27420091 |
Kyong Park1, Eunmin Seo2.
Abstract
BACKGROUND: Although Asian populations consume relatively large amounts of fish and seafood and have a high prevalence of metabolic diseases, few studies have investigated the association between chronic mercury exposure and metabolic syndrome and its effect modification by selenium.Entities:
Keywords: Asian; effect-modification; metabolic syndrome; selenium; toenail mercury
Mesh:
Substances:
Year: 2016 PMID: 27420091 PMCID: PMC4963900 DOI: 10.3390/nu8070424
Source DB: PubMed Journal: Nutrients ISSN: 2072-6643 Impact factor: 5.717
Demographic and lifestyle characteristics of study participants.
| Variables | |
|---|---|
| Age (years) | 44.83 (±0.24) |
| Sex (%) | |
| Men | 232 (46.3) |
| Women | 269 (53.7) |
| BMI (%) | |
| Underweight | 13 (2.6) |
| Normal | 231 (46.2) |
| Overweight | 138 (27.6) |
| Obesity | 118 (23.6) |
| Smoking status (%) | |
| Non-smokers | 327 (65.2) |
| Former smokers | 80 (16.0) |
| Smokers | 94 (18.8) |
| Alcohol consumption (%) | |
| Non-drinkers | 107 (21.4) |
| Drinkers | 394 (78.6) |
| Education (%) | |
| High school graduation or less | 162 (32.4) |
| College graduation or more | 338 (67.6) |
| Monthly household income (%) | |
| <3,000,000 won | 108 (21.6) |
| 3–3,990,000 won | 122 (24.4) |
| 4–4,990,000 won | 89 (17.8) |
| 5–5,990,000 won | 76 (15.2) |
| ≥6,000,000 won | 106 (21.2) |
| Residence area (%) | |
| Urban | 288 (57.5) |
| Rural | 213 (42.5) |
| MET-h/week (%) | |
| <20 | 184 (37.7) |
| 20–39 | 100 (20.5) |
| ≥40 | 204 (41.8) |
| Family history of hypertension (%) | 161 (32.3) |
| Family history of cardiovascular diseases (%) | 52 (10.5) |
| Family history of diabetes (%) | 110 (22.1) |
| Dietary supplement use (%) | 284 (56.7) |
| Toenail mercury (µg/g) | 0.40 (±0.01) |
| Toenail selenium (μg/g) | 0.69 (±0.01) |
Values are means ± standard error or n (%). BMI, body mass index; MET, metabolic equivalent.
Dietary and non-dietary correlates of toenail mercury levels 1,2.
| Variables | % Difference 3 | |
|---|---|---|
| Age (years) | 1.2 | 0.005 |
| Sex | ||
| Men | reference | |
| Women | −6.0 | 0.4 |
| BMI (kg/m2) | ||
| Underweight | reference | |
| Normal | 24.6 | 0.09 |
| Overweight | 30.5 | 0.04 |
| Obesity | 45.0 | 0.003 |
| Smoking status | ||
| Non-smokers | reference | |
| Former smokers | 14.2 | 0.09 |
| Smokers | 23.1 | 0.005 |
| Alcohol consumption | ||
| Non-drinkers | reference | |
| Drinkers | 14.8 | 0.01 |
| Monthly household income (won) | ||
| <3,000,000 | reference | |
| 3–3,990,000 | 11.1 | 0.1 |
| 4–4,990,000 | 7.0 | 0.3 |
| 5–5,990,000 | 16.8 | 0.03 |
| ≥6,000,000 | 18.2 | 0.009 |
| MET-h/week | ||
| <20 | reference | |
| 20–39 | −2.0 | 0.7 |
| ≥40 | −3.4 | 0.5 |
| Residence area | ||
| Urban | reference | |
| Rural | −0.9 | 0.8 |
| Family history of cardiovascular diseases | ||
| No | reference | |
| Yes | 9.7 | 0.2 |
| Shark and whale meat intake level (g/day) | 14.8 | <0.001 |
| Total fish intake level (g/day) 4 | 0.1 | 0.2 |
1 Multivariable-adjusted including each variable in the table; 2 Toenail mercury level was logarithmically transformed as the dependent variable for the multiple linear regression analysis; 3 Beta-coefficient is the approximate % difference in toenail mercury (ln (μg/g)) from the reference category or per unit change in the variable; BMI, body mass index; MET, metabolic equivalent; 4 The sum of 21 fish and seafood items including: mackerel, anchovy, salmon, eel, tuna (fresh and canned), pollock/cod, yellow corvina/flounder, hair tail, rock fish/yellow tail/skate ray, file fish/monk fish/naked sand lance, puffer, sea bream, squid/octopus, shellfish, whelk/gastropods/urban/marsh snail, oyster/abalone, warty sea squirt, crab, shrimp, fish paste and seafood processing byproducts (salted seafood).
Anthropometry and blood metabolic biomarkers according to the sex-specific tertiles of toenail mercury levels.
| Sex-Specific Tertile of Toenail Mercury (μg/g) | |||||||
|---|---|---|---|---|---|---|---|
| First Tertile | Second Tertile | Third Tertile | |||||
| Body mass index (kg/m2) | 22.7 | ± 0.2 | 23.0 | ± 0.2 | 24.0 | ± 0.2 | <0.001 |
| Waist circumference (cm) | 75.8 | ± 0.8 | 78.0 | ± 0.8 | 79.0 | ± 0.7 | <0.001 |
| Systolic blood pressure (mmHg) | 116.3 | ± 1.1 | 116.5 | ± 1.0 | 119.1 | ± 1.0 | <0.001 |
| Diastolic blood pressure (mmHg) | 72.4 | ± 0.8 | 72.8 | ± 0.8 | 74.4 | ± 0.8 | <0.001 |
| Fasting blood glucose (mg/dL) | 90.2 | ± 0.9 | 90.1 | ± 0.9 | 94.2 | ± 0.9 | <0.001 |
| Triglyceride (mg/dL) | 107.0 | ± 5.3 | 110.8 | ± 5.3 | 119.8 | ± 5.3 | <0.001 |
| Total cholesterol (mg/dL) | 191.2 | ± 6.8 | 207.3 | ± 6.7 | 191.6 | ± 6.8 | 0.7 |
| HDL-cholesterol (mg/dL) | 56.2 | ± 1.8 | 59.5 | ± 1.8 | 55.1 | ± 1.8 | 0.1 |
| LDL-cholesterol (mg/dL) | 113.3 | ± 2.2 | 117.9 | ± 2.2 | 116.0 | ± 2.2 | 0.2 |
Values are age-adjusted means ± standard error.
Odds ratios and 95% confidence intervals for metabolic syndrome and its components according to the sex-specific tertiles of toenail mercury levels.
| Sex-Specific Tertile of Toenail Mercury (ln (μg/g)) | ||||
|---|---|---|---|---|
| First Tertile | Second Tertile | Third Tertile | ||
| Metabolic syndrome | ||||
| Case, | 9 | 7 | 19 | |
| Model 1 | 1 | 0.78 (0.28−2.17) | 2.29 (0.99−5.31) | 0.06 |
| Model 2 | 1 | 0.84 (0.29−2.44) | 2.47 (1.01−6.08) | 0.03 |
Data are presented as odds ratio (95% confidence interval); Model 1: adjusted for age; Model 2: additionally adjusted for monthly household income, smoking status, alcohol consumption, and physical activity level.
Odds ratios (OR) and 95% confidence intervals (CI) for metabolic syndrome according to the sex-specific tertiles of toenail mercury, stratified by toenail selenium levels.
| Metabolic Syndrome 1 | Sex-Specific Tertile of Toenail Mercury (ln (μg/g)) | |||
|---|---|---|---|---|
| First Tertile | Second Tertile | Third Tertile | ||
| Toenail selenium ≤0.685 μg/g | ||||
| Case, | 4 | 3 | 12 | |
| Multivariate OR (95% CI) 1 | 1 | 0.78 (0.16−3.80) | 3.97 (1.15−13.76) | 0.02 |
| Toenail selenium >0.685 μg/g | ||||
| Case, | 5 | 4 | 7 | |
| Multivariate OR (95% CI) 1 | 1 | 0.95 (0.21−4.31) | 1.56 (0.39−6.20) | 0.5 |
1 Adjusted for age, monthly household income, smoking status, alcohol consumption, and physical activity level.